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How the COVID-19 pandemic has changed research?

Hassan karimi-maleh.

1 School of Resources and Environment, University of Electronic Science and Technology of China, Xiyuan Ave, P.O. Box 611731, Chengdu, People’s Republic of China

Elena Niculina Dragoi

2 Cristofor Simionescu Faculty of Chemical Engineering and Environmental Protection, Gheorghe Asachi Technical University, Bld. D Mangeron No. 73, 700050 Iasi, Romania

Eric Lichtfouse

3 Aix Marseille Univ, CNRS, IRD, INRAE, CEREGE, Aix-en-Provence, France

4 State Key Laboratory of Multiphase Flow in Power Engineering, Xian Jiaotong University, Xian, 710049 Shaanxi People’s Republic of China

Adversity and challenges are life's way of creating strength. Adversity creates challenge, and challenge creates change, and change is absolutely necessary for growth. If there is no change and challenge, there can be no growth and development. Willie Jolley

The coronavirus disease pandemic (COVID-19) started in 2019 and induced long-lasting effects on many aspects of life. Every one of us felt how the quiet existence was transformed into a chaotic state full of uncertainties, doubts, and fear for one’s safety. This led to many societal changes, some influenced by objective facts and events, others by human risk perception and behavior modifications. Although risk perception tends to be biased and the responses of individuals to the perceived threat are very different, jumping from lack of precautions and a false feeling of security to unnecessary scares and stigmatization of risks groups will impact human activities in all areas for many years to come (Brug et al. 2009 ). Here, we review the positive and negative outcomes of the pandemic on academia and scientific enterprises.

Research disruption

The government's drastic measures, especially in the early days of the pandemic, led to the closure of many laboratories. The discontinuation of experiments caused the loss of data and, in turn, shrank financial and material resources. In addition, the potential for scientific innovation was significantly hampered by travel restrictions, and by less face-to-face meetings, conferences, and workshops (Subramanya et al. 2020 ). Although few argue the importance of precautions to slow the spread of diseases, the pandemic policies significantly disrupted both professional and personal lives. The adverse effects of the pandemic on academia and scientific enterprises resulted from the closure of laboratories, the reduction of avenues for conducting research in a collaborative and direct manner, and the limitation of direct dissemination of results to peers. These major issues prompted changes in research time allocation, publication behavior, and funding in a domino fall-like way.

Impact on publication

Publishing is essential for researchers because, whatever criticisms are currently raised against the use of publication metrics, an academic career is closely correlated to the quality and frequency of publications. During the first COVID year of 2020, the average self-reported number of publication metrics for the USA and Europe was slightly lower than in 2019 (Gao et al. 2021 ). However, this perceived reduction is not general, and publication number varied with country, institution, and discipline. For example, medical-based publications showed a 6.5-fold increase, while non-medical publications decreased by 10–12% (Riccaboni and Verginer 2022 ). In the engineering field, for the School of Resources and Environment of the University of Electronic Science and Technology of China, a Scopus search indicates a slight reduction of publication number in 2020, of 163, compared to 165 in 2019, while in 2021, the number raised to 243. The same search procedure applied to the Cristofor Simionescu Faculty of Chemical Engineering and Environmental Protection from Gheorghe Asachi Technical University shows a rise from 36 articles in 2019 to 63 articles in 2020 and 73 articles in 2021.

Less experimental time

A strong impact of the discipline field on research time was observed. For instance, research time declined by 30–40% versus pre-pandemic levels in research heavily relying on physical laboratories and experiments such as biological sciences and chemical engineering (Myers et al. 2020 ). This reduction is not only due to the lack of on-site access but also to staff shortage and supply-chain issues for materials, spare parts, and protective equipment (Sohrabi et al. 2021 ). As the measures relaxed and more protective equipment became available, laboratory work improved slowly to return to a ‘new normal’ functioning where the measures and the management of the protective equipment are still essential (Yang et al. 2022 ; Ufnalska and Lichtfouse 2021 ; Gorrasi et al. 2021 ). Nevertheless, the self-reported working hours decreased by 11%, and the reduction of time allocated to research was about 24% (Myers et al. 2020 ). Consequently, most tasks were performed at home, sometimes in unsuitable conditions, with spouses and kids wandering around. The work at home focused more on data analysis, manuscript, and proposal writing.

Research advancement was slowed down, particularly for early-stage career scientists, due to reduced laboratory access, less direct teamwork, and meeting cancelation. The delay or cancellation of research opportunities and the impaired ability to collect and analyze data led to a decreased ability to work. According to a survey in the UK, 50% of responders reported being very stressed, and 75% were apprehensive about their future plans (Byrom 2020 ). This survey also revealed that only 12% of final-year doctoral students had an option to extend their studies, which put additional pressure on an already at-risk group.

Fund redirection

The pandemic also reduced the number of projects. For example, in the USA and Europe, the number of respondents claiming that they had no new project increased from 9% in 2019 to 27% in 2020 (Gao et al. 2021 ). Research topics were also strongly modified by redirecting funds toward COVID issues, with many classical clinical trials being temporarily stopped in vulnerable, low-income countries (Subramanya et al. 2020 ). Specifically, in July 2020, about 1200 clinical trials were suspended because clinical scientists had no or reduced access to healthcare research infrastructures (Riccaboni and Verginer 2022 ). Moreover, drastic budget cuts also occurred in other areas, such as cancer research. For instance, 45 million pounds were cut in the UK, inducing a substantial decline in fellowships and research programs for hundreds of scientists (Burki 2021 ). Here, early-career scientists are at risk because institutions are not hiring new personnel.

The redeployment of private and public funds to COVID-related concerns has substantially increased the number of investigations in this field. For instance, in May 2020, shortly after the pandemic outbreak, 1,221 COVID studies were declared in the international clinical trial registry (Bramstedt 2020 ). Nevertheless, research misconduct increased rapidly as an unwanted consequence of the rapid pace imposed by the pandemic and available funds. Indeed, 33 articles were already considered unsuitable in May 2020 (Bramstedt 2020 ). Ironically, the overflow of funds is as much a curse as the lack of funds, as it uncovers new problems and exacerbates existing issues. Crowdfunding, a popular fund-raising means commonly used by the public, was explored by academia for the first time during the pandemic. However, researchers did not favor this approach due to the somewhat different rules that must be applied and the limited amount of money compared with the standard sources (Sultan et al. 2022 ).

The personal living conditions of scientists have also dropped research efficiency. Indeed, the balance between work and free time has been utterly disrupted during the pandemic. Moreover, researchers who did not fit the classical profile of the ideal academic career—the traditional man with his traditional wife—have been under additional pressure in the context of unrealistic expectations for tenure or promotion (King and Frederickson 2021 ). In addition, female academics had difficulty balancing the expected primary role of caregiver with the role of the scientist, leading to an overall reduction in female publications compared with men (Alam et al. 2021 ). For example, in the first ten weeks of lockdown, the academic productivity of women dropped 13.2% compared to that of male academics in the USA. This productivity gap occurred in various countries and was more pronounced for assistant professors and top-ranked institutions (Cui et al. 2022 ). In several academic journals, the reduction in the proportion of published articles by women was confirmed in the summer of 2020 (Pereira 2021 ). Analyzing tweets, similar trends were observed in social media (Kim and Patterson 2022 ).

Elitism discrimination, a form of inequality, was exacerbated by the pandemic. In this context, elitism discrimination indicates the cases where results or scientists from less prestigious institutions are considered of lower quality. One example is the discrepancy between the number of vaccines approved by the European Medicines Agency versus the World Health Organization, where some vaccines were considered inadequate for the former. This has led to confusion, skepticism, and an increased sense of injustice (Sikimić 2022 ).

Online adaptation

To mitigate research issues arising from the pandemic, research institutions strongly reinforced techniques allowing online work and collaboration by video-conferencing. For example, new portals for sharing scientific data, such as the European COVID-19 Data Portal, emerged, and conferences and workshops were held online (Korbel and Stegle 2020 ). Social media were also found to facilitate the dissemination of information. However, curating data effectively and extracting meaningful information from social media remains a challenge.

Despite shutdowns, electronic communications systems allowed researchers to participate in various collaborative endeavors (Korbel and Stegle 2020 ). Due to its effectiveness, electronic communication was initially targeted at COVID research and then rapidly transferred to most research disciplines. Sometimes, work unfinished in the lab was enhanced by exchanging information with theoretical researchers, improving the quality of published articles. In other words, online work allows more time to think compared with experimental work, where scientists, in particular students, tend to jump rapidly from one experiment to another without taking the time to explore the meaning of their results in depth.

Figure  1 depicts the main changes induced by the pandemic in 2020. Before the pandemic, collaboration was done face-to-face with information shared within local groups. At that time, computers were mainly used to improve presentation. Although online tools were already available, e.g., for online teaching and research discussions, they were rarely used by universities. Moreover, data storage database processing was done mainly in local servers and computers. During the pandemic, we observed sharp and rapid changes such as an intense development of online tools for meetings, teaching, cloud storing, data sharing, and social media. As a result, platforms such as Zoom, Google Meet, or Microsoft Teams registered an unprecedented rise in the number of users and services provided. This allowed a tighter connection between people in different areas and demonstrated that even the most change-resistant institutions could adopt new technologies when needed.

Research before the pandemic in 2019 involved mainly local meetings, teaching, experiments, computers, and servers. The pandemic in 2020 has fostered remote meetings, distant teaching, international collaboration, and the use of cloud services

The conference format underwent significant changes during the pandemic. Due to the various restrictions, most topical conferences were suspended or transformed into online meetings. On-site laboratory and project meetings were rapidly converted into online sessions. Indeed, these types of gatherings are essential for learning, dissemination, and creating collaboration. Virtual meetings presented advantages such as easy accessibility to many individuals located anywhere, and reduced meeting organization and participant accommodation costs (Reinhard et al. 2021 ). These meetings have fostered international collaboration. Moreover, virtual conferences display a much lower environmental price (Donlon 2021 ). Virtual conferences also save much traveling time. These benefits make virtual meetings attractive to young scientists and underfunded academics from developing countries. Social media tools allow for the improvement of the attractiveness of these events. For example, backchannels on Twitter enhance immersion and communication, live streams increase awareness, and video recordings and archiving perpetuate information availability (Atkinson 2009 ). However, a virtual conference environment does not provide the same level of social networking, camaraderie, and connection that an in-person conference can offer (Reinhard et al. 2021 ). Nevertheless, virtual conferencing must not be dismissed, and a mixed format of both online and in-person meetings is promising for future research.

Overall, although the COVID pandemic induced adverse effects on many societal aspects, the lockdowns stimulated a rapid adaptation of research with the development of online practices that will undoubtedly improve research.

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Contributor Information

Hassan Karimi-Maleh, Email: nc.ude.ctseu@nassah .

Elena Niculina Dragoi, Email: [email protected] .

Eric Lichtfouse, Email: [email protected] .

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• 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.

This research received no external funding.

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University Hospital and School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

Israel Júnior Borges do Nascimento & Milena Soriano Marcolino

Medical College of Wisconsin, Milwaukee, WI, USA

Israel Júnior Borges do Nascimento

Helene Fuld Health Trust National Institute for Evidence-based Practice in Nursing and Healthcare, College of Nursing, The Ohio State University, Columbus, OH, USA

Dónal P. O’Mathúna

School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland

Department of Anesthesiology, Intensive Care and Pain Medicine, University of Münster, Münster, Germany

Thilo Caspar von Groote

Department of Sport and Health Science, Technische Universität München, Munich, Germany

Hebatullah Mohamed Abdulazeem

School of Health Sciences, Faculty of Health and Medicine, The University of Newcastle, Callaghan, Australia

Ishanka Weerasekara

Department of Physiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka

Cochrane Croatia, University of Split, School of Medicine, Split, Croatia

Ana Marusic, Irena Zakarija-Grkovic & Tina Poklepovic Pericic

Center for Evidence-Based Medicine and Health Care, Catholic University of Croatia, Ilica 242, 10000, Zagreb, Croatia

Livia Puljak

Cochrane Brazil, Evidence-Based Health Program, Universidade Federal de São Paulo, São Paulo, Brazil

Vinicius Tassoni Civile & Alvaro Nagib Atallah

Yorkville University, Fredericton, New Brunswick, Canada

Santino Filoso

Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada

Nicola Luigi Bragazzi

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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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Research Article

Impact of COVID-19 pandemic on mental health: An international study

Roles Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

¶ ‡ ATG, MK and AK designed and implemented the study together. AK and MK should be considered joint senior authors.

Affiliation Division of Clinical Psychology & Intervention Science, Department of Psychology, University of Basel, Basel, Switzerland

Roles Data curation, Formal analysis, Writing – original draft, Writing – review & editing

Affiliation Department of Health Sciences, European University Cyprus, Nicosia, Cyprus

Roles Investigation, Resources, Writing – review & editing

Affiliation Psychological Laboratory, Faculty of Public Health and Social Welfare, Riga Stradiņš University, Riga, Latvia

Affiliation Kore University Behavioral Lab (KUBeLab), Faculty of Human and Social Sciences, Kore University of Enna, Enna, Italy

Affiliation Department of Social Sciences, School of Humanities and Social Sciences, University of Nicosia, Nicosia, Cyprus

Affiliation Department of Nursing, Cyprus University of Technology, Limassol, Cyprus

Affiliation Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus

Affiliation Department of Psychological Counseling and Guidance, Faculty of Education, Hasan Kalyoncu University, Gaziantep, Turkey

Affiliation The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong

Affiliation Department of Psychology, Fundación Universitaria Konrad Lorenz, Bogotà, Columbia

Roles Conceptualization, Investigation, Resources, Writing – review & editing

Affiliation Faculty of Psychology, University of La Sabana, Chía, Columbia

Affiliation School of Applied Psychology, University College Cork, Cork, Ireland

Affiliation School of Psychology, University College Dublin, Dublin, Ireland

Affiliation Medical University Innsbruck, Innsbruck, Austria

Affiliation Department of Psychology, Babeş-Bolyai University (UBB), Cluj-Napoca, Romania

Affiliation Instituto Superior de Psicologia Aplicada (ISPA), Instituto Universitário; APPsyCI—Applied Psychology Research Center Capabilities & Inclusion, Lisboa, Portugal

Affiliation Faculdade de Psicologia, Alameda da Universidade, Universidade de Lisboa, Lisboa, Portugal

Affiliation LIP/PC2S, Université Grenoble Alpes, Grenoble, France

Affiliation Department of Biomedicine, Biotechnology and Public Health, University of Cadiz, Cadiz, Spain

Affiliation Instituto ACT, Madrid, Spain

Affiliation Department of Psychology, European University of Madrid, Madrid, Spain

Affiliation Department of Psychology and Sociology, University of Zaragoza, Zaragoza, Spain

Affiliation Vadaskert Child and Adolescent Psychiatric Hospital, Budapest, Hungary

Affiliation Private Pratice, Poland

Affiliation Department of Psychology, University of Jyväskylä, Jyväskylä, Finland

Affiliation Clinic for Psychiatry, Clinical Center of Montenegro, Podgorica, Montenegro

Affiliation Ljubljana University Medical Centre, Ljubljana, Slovania

Affiliation Département de Psychologie, Université du Québec à Trois-Rivières, Trois-Rivières, Canada

Affiliation Department of Psychiatry and Behavioral Science, Duke University, Durham, North Carolina, United States of America

Roles Conceptualization, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

Affiliation Department of Psychology, University of Cyprus, Nicosia, Cyprus

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• Andrew T. Gloster, 
• Demetris Lamnisos, 
• Jelena Lubenko, 
• Giovambattista Presti, 
• Valeria Squatrito, 
• Marios Constantinou, 
• Christiana Nicolaou, 
• Savvas Papacostas, 
• Gökçen Aydın, 

• Published: December 31, 2020
• https://doi.org/10.1371/journal.pone.0244809
• Reader Comments

The COVID-19 pandemic triggered vast governmental lockdowns. The impact of these lockdowns on mental health is inadequately understood. On the one hand such drastic changes in daily routines could be detrimental to mental health. On the other hand, it might not be experienced negatively, especially because the entire population was affected.

The aim of this study was to determine mental health outcomes during pandemic induced lockdowns and to examine known predictors of mental health outcomes. We therefore surveyed n = 9,565 people from 78 countries and 18 languages. Outcomes assessed were stress, depression, affect, and wellbeing. Predictors included country, sociodemographic factors, lockdown characteristics, social factors, and psychological factors.

Results indicated that on average about 10% of the sample was languishing from low levels of mental health and about 50% had only moderate mental health. Importantly, three consistent predictors of mental health emerged: social support, education level, and psychologically flexible (vs. rigid) responding. Poorer outcomes were most strongly predicted by a worsening of finances and not having access to basic supplies.

Conclusions

These results suggest that on whole, respondents were moderately mentally healthy at the time of a population-wide lockdown. The highest level of mental health difficulties were found in approximately 10% of the population. Findings suggest that public health initiatives should target people without social support and those whose finances worsen as a result of the lockdown. Interventions that promote psychological flexibility may mitigate the impact of the pandemic.

Citation: Gloster AT, Lamnisos D, Lubenko J, Presti G, Squatrito V, Constantinou M, et al. (2020) Impact of COVID-19 pandemic on mental health: An international study. PLoS ONE 15(12): e0244809. https://doi.org/10.1371/journal.pone.0244809

Editor: Joel Msafiri Francis, University of the Witwatersrand, SOUTH AFRICA

Received: October 3, 2020; Accepted: December 16, 2020; Published: December 31, 2020

Copyright: © 2020 Gloster et al. 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: All relevant data are within the paper and its Supporting Information files.

Funding: This work was supported by grants from the Swiss National Science Foundation awarded to Andrew T. Gloster (PP00P1_ 163716/1 & PP00P1_190082). The funder provided support in the form of salaries for authors [ATG], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. One of the authors is employed by a commercial affiliation: Private Pratice, Poland. This affiliation provided support in the form of salaries for authors [BK], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: One of the authors is employed by a commercial affiliation: Private Pratice, Poland. This affiliation provided support in the form of salaries for author BK, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials. No other authors have competing interests to declare.

Introduction

The COVID-19 global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus triggered governmentally mandated lockdowns, social distancing, quarantines and other measures in the interest of public health. The mandated lockdowns abruptly and dramatically altered people’s daily routines, work, travel, and leisure activities to a degree unexperienced by most people living outside of war zones. Simultaneously, the highly contagious, yet invisible virus transformed previously neutral situations to perceived potentially dangerous ones: social interaction, touching one’s face, going to a concert, shaking someone’s hand, and even hugging grandparents. Given these changes and looming threat, increases in anxiety and depression can be expected [ 1 ]. Indeed, common psychological reactions to previous quarantines include post-traumatic symptoms, confusion, and anger [ 2 ], though these data stem from quarantines of specific regions or a subgroup of exposed people, such as medical professionals. It therefore remains an empirical question whether such patterns are consistent when entire populations across the globe are simultaneously affected.

For most people, it stands to reason that governmentally mandated lockdowns decrease their activity levels and the number of stimuli experienced compared to pre-lockdown levels. The impact of reducing activities, stimuli and routines on the population is unknown, but various analogue situations can be used to make predictions, like death of a spouse [ 3 ]; hearing loss [ 4 ]; job loss [ 5 ]; long duration expeditions [ 6 ]; poor acculturation [ 7 ]; and even ageing when combined with loneliness [ 8 ]. Each of these situations is associated with increases in psychological distress. This reduction of stimulations may lead to boredom and reductions in reinforcement, which has been associated with depression [ 9 ]. The sum total of these literatures, and some evidence from country specific studies on COVID-19 suggests that for some people, the mental distress in the form of stress, depression, and negative affect are likely reactions to the lockdown; therefore, people’s wellbeing is likely to suffer. Indeed, increased loneliness, social isolation, and living alone are associated with increased mortality [ 10 ]–the exact effect that mandated lockdown and social distancing rules aimed to counteract.

Alternately, the planned slowing down of daily routines can be beneficial. For example, vacations and weekends are highly sought-after–if not always achieved–periods of relaxation and stress reduction [ 11 ]. Likewise, some religious and spiritual traditions encourage simplicity, mindfulness, and solitude with the goal of increasing wellbeing [ 12 ]. It is therefore conceivable that for some people the lockdown could offer a reprieve from daily hassles and stress and even lead to increases in wellbeing. It is therefore equally important to identify protective factors that can buffer against the negative effects of the lockdown.

Although nearly all people around the globe have been subject to some form of lockdown measures to contain the COVID-19 response, variations exist with respect to how each person is confined, even within a single country. For instance, during the COVID-19 pandemic some people were allowed to go to work, whereas others were required to work exclusively from home. For various reasons, some people had difficulty obtaining some basic supplies. Further, some were thrust into the situation of taking care of others (e.g., children, due to closing of schools). Finally, some people lost income as a result of the lockdown, and this is a known risk-factor for poor mental health [ 13 , 14 ]. Finally, a lockdown may be experienced differently the longer it continues and potentially when in confined spaces [ 2 ]. All of these lockdown-specific features may have an impact on one’s mental health, but to date it remains inadequately explored.

As the risk of the pandemic continues, it is important to understand to what degree the virus-induced uncertainty and the lockdown-induced changes in daily routines impact stress, depression, affect, and wellbeing. Towards this end, it is important to identify factors that can mitigate potential negative psychological effects of pandemics and lockdowns. Various social and psychological factors have been identified in other contexts that may also help build resilience in large-scale pandemics such as COVID-19. On the social level, one such candidate is social support, which has repeatedly been found to positively impact mental health and wellbeing [ 15 – 18 ]. Another social factor is the family climate and family functioning, which clearly impacts people’s mental health [ 19 , 20 ]. Psychological factors such as mindfulness and psychologically flexible response styles (as opposed to rigid and avoidant response styles) are behavioral repertoires that have previously been shown to buffer the impact of stress and facilitate wellbeing [ 21 – 24 ].

Given the scope of the COVID-19 pandemic, it is crucial to better understand how a pandemic and associated lockdowns impact on mental health. Thus, the aim of this study was to determine mental health outcomes and to examine known predictors of outcomes to identify psychological processes and contextual factors that can be used in developing public health interventions. It can be assumed, but remains untested, that those with risks in social-demographic factors, living conditions, social factors and psychological factors have more severe reactions to the lockdown. We therefore tested whether outcomes of stress, depression, affect, and wellbeing were predicted by country of residence, social demographic characteristics, COVID-19 lockdown related predictors, social predictors, and psychological predictors.

Participants

The inclusion criteria were ≥18 years of age and ability to read one of the 18 languages (English, Greek, German, French, Spanish, Turkish, Dutch, Latvian, Italian, Portuguese, Finnish, Slovenian, Polish, Romanian, Hong Kong, Hungarian, Montenegrin, & Persian.). There were no exclusion criteria. People from all countries were eligible to participate.

Ethics approval was obtained from the Cyprus National Bioethics Committee (ref.: EEBK EΠ 2020.01.60) followed by site approvals from different research teams involved in data collection. All participants provided written informed consent prior to completing the survey (computer-based, e.g., by clicking “yes”).

A population based cross-sectional study was conducted in order to explore how people across the world reacted to the COVID-19. The anonymous online survey was distributed using a range of methods. Universities emailed the online survey to students and academic staff and also posted the survey link to their websites. In addition, and in order to broaden the sample to older age groups and to those with different socio-demographic characteristics, the survey was disseminated in local press (e.g., newspapers, newsletters, radio stations), in social media (e.g., Facebook, Twitter, etc.), in professional networks, local hospitals and health centers and professional groups’ email lists (e.g., medical doctors, teachers, engineers, psychologists, government workers), and to social institutions in the countries (e.g., churches, schools, cities/townships, clubs, etc.).

Data were collected for two months between 07th April and 07th June 2020. The majority of countries where data were collected had declared a state of emergency for COVID-19 during this time.

Well validated and established measures were used to assess constructs. When measures did not already exist in a language, they were subject to forward and backward translation procedures. Well-validated measures of predictors and outcomes and items measuring COVID-19 related characteristics were selected after a consensus agreement among the members of this study.

Respondents’ countries were coded and entered as predictors.

Socio-demographic status.

Participants responded to questions related to their socio-demographic characteristics including their age, gender, country of residence, marital status, employment status, educational level, whether they have children as well as their living situation.

Lockdown variables.

Participants responded to questions related to lockdown including length of lockdown, whether they need to leave home for work, any change in their finances, whether they were able to obtain basic supplies, the amount of their living space confined in during the lockdown. They were also asked whether they, their partner, or a significant other was diagnosed with COVID-19.

Social factors.

Social factors were measured using the Brief Assessment of Family Functioning Scale (BAFFS; [ 25 ]) and the Oslo Social Support Scale (OSSS; [ 26 ]). The BAFFS items are summed to produce a single score with higher scores indicating worse family functioning. The OSSS items are summed up and provide three levels types of social support: low (scored 3–8), moderate (scored 9–11) and high (scored 12–14).

Psychological factors.

Psychological factors including mindfulness and psychological flexibility. Mindfulness was measured using the Cognitive Affective Mindfulness Scale (CAMS; [ 27 ]). The CAMS produces a single score with higher scores indicating better mindfulness qualities. Psychological flexibility (e.g., hold one’s thoughts lightly, be accepting of one’s experiences, engage in what is important to them despite challenging situations) was measured using the Psyflex scale [ 28 ]. The Psyflex produces a single score with higher scores indicating better psychological flexibility qualities.

Stress was measured using the Perceived Stress Scale (PSS; [ 29 ]). The PSS assesses an individual’s appraisal of how stressful situations in their life are. Items ask about people’s feelings and thoughts during the last month. A total score is produced, with higher scores indicating greater overall distress.

Depression.

Depressive symptomatology was assessed using two items from the disengagement subscale of the Multidimensional State Boredom Scale (MSBS; [ 30 ]). These items assessed wanting to do pleasurable things but not finding anything appealing (i.e., boredom), as well as wasting time. Based on concepts of reinforcement deprivation (i.e., lack of access to or engagement with positive stimuli) that is known to contribute to depression, we added an item that measured how rewarding or pleasurable people found the activities that they were engaging in (i.e., reinforcement). Higher scores indicated higher depressive symptomatology.

Positive affect/ negative affect.

The Positive And Negative Affect Scale (PANAS) was used to measure affect [ 31 ]. The original version of the questionnaire was used with five additional items: bored, confused, angry, frustrated and lonely. All items were scored on a 5-point Likert type scale, ranging from 1 = very little/not at all to 5 = extremely and summed up so that higher scores in the positive-related items indicating higher positive affect and higher scores in the negative-related items indicating higher negative affect. In order to capture additional dimensions of negative affect believed to be relevant to the COVID-19 lockdowns, we additionally added five items: bored, confused, angry, frustrated, lonely.

Wellbeing was assessed using the Mental Health Continuum Short Form (MHC-SF; [ 32 ]); which assesses three aspects of wellbeing: emotional, psychological, and social. The MHC-SF produces a total score and scores for each of the three aspects of wellbeing. The MHC-SF can also be scored to produce categories of languishing (i.e., low levels of emotional, psychological, and social well-being), flourishing (i.e., high levels of emotional psychological and social well-being almost every day), and moderately mentally healthy (in between languishing and flourishing).

Statistical analysis

The mean and standard deviation was calculated for dependent variables that follow the normal distribution while the median and interquartile range (IQR) were computed for non-normally distributed data. Bivariable association between an outcome variable and each predictor was investigated with ANOVA test for categorical predictor and univariable linear regression for numerical predictor. Linear mixed-effect model with random effect for country was performed to consider simultaneously several predictors in the same model and to account for the variation in outcome variable between countries. Four separate linear mixed-effect models were used for each outcome variable, one for each set of socio-demographic, lockdown, social and psychosocial predictors and multicollinearity for each set of predictors was investigated with the variation inflation criterion (VIF). Standardized regression coefficients were computed as effect size indices to measure the strength of the association between predictor variables and outcome variables. The comparison between the country mean and overall mean for each outcome variable was estimated though a linear regression model with dependent variable the mean centering outcome and predictor the country. Cohen’s d effect size of the standardize difference between country mean and the overall mean was computed as a measure of the magnitude of the difference between the two means.

The whole sample was used in linear mixed-effect models while for the comparison of country mean to the overall mean was used the sample from countries with sample size ≥100. The R packages lme4 and effect sizes were used for fitting the linear mixed effect model and to compute the standardized regression coefficients of the linear mixed effect models [ 33 ]. Significance test and confidence intervals were calculated at a significance level of 0.05. The following cut-off values were used for the evaluation of the effect sizes: ‘tiny’ ≤0.05, ‘very small’ from 0.05 to ≤0.10, ‘small’ from 0.10 to ≤ 0.20, ‘medium’ from 0.20 to ≤ 0.30, ‘large’ from 0.30 to ≤ 0.40 and ‘very large’ > 0.40 [ 34 ].

Descriptive

Participants were n = 9,565 people from 78 countries. See supporting information for a participation flowchart ( S1 Appendix ). The countries with the largest samples were: Latvia (n = 1285), Italy (n = 962), Cyprus (n = 957), Turkey (n = 702), Switzerland (n = 550), Hong Kong (n = 516), Colombia (n = 485), Ireland (n = 414), Austria (n = 368), Romania (n = 339), Portugal (n = 334), France (n = 313), Spain (n = 296), Germany (n = 279), Hungary (n = 273), Greece (n = 270), USA (n = 268), Finland (n = 157), Montenegro (n = 147), Poland (n = 135), United Kingdom (n = 100), Slovenia (n = 77), and Canada (n = 60). The remaining countries are listed in the supporting information ( S1 Table ).

Outcome variables

The means, standard deviations, and where appropriate percentage of participants within categories of the five outcome variables can be seen in Table 1 .

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https://doi.org/10.1371/journal.pone.0244809.t001

Predictor variables

A full list of countries can be found in the supporting information ( S1 Table ).

The mean age was 36.9 (13.3) years. A majority of participants were female (77.7%), approximately a fifth male (22.0%), and small minority identified as other (0.3%). More than half of the respondents were either in a relationship (25.7%) or married (36.1%), almost a third were single (30.8%), and the rest were either divorced (5%), widower (1.1%) or other (1.3%). Participants indicated that they lived: alone (14.6%), with both parents (20.8%), one parent (5.1%), with their own family including partner and children (54.1%), or with friends or roommates (5.5%). Less than half of respondents had children (40.8%). Approximately half of the participants were working full time (53.4%), almost a fifth were working part-time (17.5%), 23.2% were unemployed and a small minority were either on parental leave (2.2%) or retired (3.7%).

COVID-19 lockdown variables.

At the time of responding, participants were in lockdown or self-isolation for a median of 5.0 (3.0 IQR) weeks. Most people indicated that they had not been infected with COVID-19 (88.0%), a small minority indicated they had been infected (1.4%) and the rest had symptoms but were unsure (10.6%). Similar patterns were seen with reported infection rates of partners (no: 92.2%, yes: 0.7%, unsure: 7.1%) and of people close to them (no: 86.0%; yes: 5.6%; unsure: 8.4%). With respect to leaving the house for work, almost half (47.7%) indicated that this never occurred, 7.7% indicated leaving only once, whereas an almost equal number indicated leaving a couple times per week (23.7%) or more than three times per week (21.0%). Nearly all participants indicated they were able to obtain all the basic supplies they needed (93.5%). Participants reported having a median inner living space of 90.0 square meters (80.0 IQR) and median outdoor space of 20.0 square meters (192.1 IQR). Finally, with respect to finances, more than half indicated that their financial situation remained about the same (57.9%), a minority indicated it improved (8.9%), and a third reported that their finances had gotten worse (33.3%).

Social and psychological predictors.

Mean values of the other predictors (i.e., social predictors and psychological predictors) can be seen in Table 1 .

Multivariate analyses

Results of multivariate analyses for the outcome of stress can be seen in Table 2 . The largest protective factor against stress was social support (high support vs low support (-3.35, 95%CI, -3.39 to -2.92), with a very large effect size). Positive predictors of stress with large effect sizes were being female (2.42, 95%CI, 2.07 to 2.77) and worsening of finances (2.32, 95%CI, 1.68 to 2.96), whereas psychological flexibility buffered this response (-0.65, 95%CI, -0.69 to -0.62). Higher education levels were also associated with lower levels of stress, with a large effect size (see Table 2 ). Moderate effect sizes for predictors associated with less stress were older age (-0.13, 95%CI, -0.14, -0.11) and mindfulness (-0.69, 95%CI, -0.74, -0.64). Moderate effect sizes of predictors associated with more stress were worse family functioning (0.98, 95%CI, 0.90, 1.06) and not being able to obtain all basic supplies (1.82 95%CI, 1.12, 2.52).

https://doi.org/10.1371/journal.pone.0244809.t002

Differences in reported levels of stress across countries were largely negligible, with the exception of two countries that reported higher levels of stress (Hong Kong (2.85, 95%CI, 2.22, 3.49) and Turkey (2.47, 95%CI, 1.93, 3.02)) and two that reported lower levels of stress (Portugal (-2.50, 95%CI, -3.29, -1.71) and Montenegro (-3.30, 95%CI, -4.49, -2.11)) than the average stress level across all countries. See supporting information for information on each country ( S2 – S6 Tables).

Results of multivariate analyses for the outcome of depression can be seen in Table 3 . The strongest predictor of depression was social support, such that high (-1.30, 95%CI, -1.44, -1.16) and medium levels (-0.73, 95%CI, -0.85, -0.62) of social support were protective against depression (relative to low levels) with a very large and large effect sizes, respectively. The only other large effect size was for psychological flexibility, which also served in a protective manner (-0.20, 95%CI, -0.22, -0.19). Moderate effect sizes of predictors associated with less depression symptoms were also observed for higher education levels (see Table 3 ). Moderate effect sizes of predictors associated with more depression were worse family functioning (0.29, 95%CI, 0.27, 0.32) and not being able to obtain all basic supplies (0.49, 95%CI, 0.27, 0.70).

https://doi.org/10.1371/journal.pone.0244809.t003

The amount of depression symptoms reported on average within countries was similar for most countries with the exception of one country with lower reported levels than average with a large effect size (Austria (-0.71, 95%CI, -0.95, -0.47)) and one with higher levels than average with a large effect size (USA (0.85, 95%CI, 0.58, 1.13)). See supporting information for information on each country ( S2 – S6 Tables).

Results of multivariate analyses for the outcome of affect can be seen in Table 4 . With respect to positive affect, social support (high support vs low support (5.69, 95%CI, 5.23, 6.16) and psychological flexibility (0.77, 95%CI, 0.74, 0.81) were both predictors with very large effect sizes. Interestingly, those who left their house more than three times per week had higher levels of positive affect than those that did not leave their house for work (1.68, 95%CI, 1.18, 2.17), with a medium effect size. Higher education levels were associated with higher levels of positive affect with a medium to large effect size (see Table 4 , PANAS-Positive).

https://doi.org/10.1371/journal.pone.0244809.t004

The amount of positive affect reported on average within countries was similar for most countries with the exception of one country with lower reported levels than average with a large effect size (Finland (-2.96, 95%CI, -4.19, -1.73)) and one with higher reported levels than average with a large effect size (Portugal (2.96, 95%CI, 2.12, 3.80)). See supporting information for information on each country ( S2 – S6 Tables).

With respect to negative affect, social support (high support vs low support (-2.74, 95%CI, -3.2, -2.29) and psychological flexibility (-0.62, 95%CI, -0.66, -0.58) were again the strongest associated predictors, with large effects. Higher education levels were also associated with lower levels of negative affect, with a medium effect (see Table 4 , PANAS-Negative). Higher levels of negative affect were noted, with medium effect sizes, for the predictors: worsening of finances (1.75, 95%CI, 1.10, 2.40) and not being able to obtain all basic supplies (1.6, 95%CI, 0.89, 2.31).

The amount of negative affect reported on average within countries was similar for most countries with the exception of few countries with lower reported negative affect levels than average with a very large effect sizes (Switzerland (-4.96, 95%CI, -5.91, -4.01), Germany (-4.70, 95%CI, -6.03, -3.37) & Austria (-6.49, 95%CI, -7.65, -5.33)) and one with a large effect size (Montenegro (-3.56, 95%CI, -5.39, -1.73). The average amount of negative affect was higher than average in two countries, with very large effects size (Turkey (5.75, 95%CI, 4.92, 6.59) & Finland (7.57, 95%CI, 5.80, 9.34)). See supporting information for information on each country ( S2 – S6 Tables).

Results of multivariate analyses for the outcome of wellbeing can be seen in Table 5 . Once again, social support (high support vs low support (13.20, 95%CI, 12.39, 14.01)) and psychological flexibility (1.42, 95%CI, 1.34, 1.49) were the predictors with the largest effect sizes (very large) on wellbeing. Higher education levels were associated with higher levels of wellbeing with a medium to large effect sizes (see Table 5 ). Medium negative effect sizes were noted for family functioning (-1.98, 95%CI, -2.12, -1.83) and inability to obtain all basic supplies (-3.27, 95%CI, -4.67, -1.87). Two medium positive effect sizes were observed: mindfulness (0.95, 95%CI, 0.86–1.04) and living with friends/roommates ((3.04, 95%CI, 1.59, 4.48), relative to living alone).

https://doi.org/10.1371/journal.pone.0244809.t005

The level of wellbeing reported on average within countries was similar for most countries with the exception of three countries with higher levels with large effect sizes (Austria (4.95, 95%CI, 3.55, 6.34), Finland (5.24, 95%CI, 3.10, 7.38), & Portugal (4.59, 95%CI, 3.12, 6.05)) and two countries with lower levels of wellbeing than average with large (Italy (-4.36, 95%CI, -11.06, 2.35)) and very large effect sizes (Hong Kong (-6.84, 95%CI, -8.02, -5.66)). See supporting information for information on each country ( S2 – S6 Tables).

The COVID-19 is the largest pandemic in modern history. This study assessed nearly 10,000 participants across many countries to examine the impact of the pandemic and resultant governmental lockdown measures on mental health. During the height of the lockdown, the pandemic was experienced as at least moderately stressful for most people, and 11% reported the highest levels of stress. Symptoms of depression were also high, including 25% of the sample indicating that the things they did were not reinforcing, 33% reporting high levels of boredom, and nearly 50% indicating they wasted a lot of time. Consistent with symptoms of stress and depression, 10% of participants were psychologically languishing. These results suggest that there is a subgroup of people who are especially suffering and that in about 50% of the respondents’ levels of mental health was only moderate. Previous studies have found that along with low levels, even moderate levels of mental health (which consists of only moderate levels of emotional, psychological, and social well-being) are associated with increased subsequent disability, productivity loss, and healthcare use [ 35 – 37 ]. Not everyone was suffering, however, as evidenced by the nearly 40% of participants who reported levels of mental health consistent with flourishing. The present results, while serious, do not point to more severe reactions observed in previous samples of selective quarantined individuals or groups [ 2 ]. Perhaps the previously reported distress in these groups is prevented when an entire country or world is in lockdown so that the feeling emerges that “everyone is in it together”.

Importantly, a handful of predictors emerged that consistently predicted all outcomes: Social support, education level, finances, access to basic needs, and the ability to respond psychologically flexible. The consistency of results examining predictors is noteworthy, both in terms of the consistently strong predictors (e.g., social support, education, psychological flexibly, as well as loss of income and lack of access to necessities) and in terms of the other predictors that were either not predictive or only weakly so. All predictors were chosen based on theoretical ties to the outcomes, previous findings, and studies on quarantines [ 2 ].

A novel finding was that people who left their house three or more times per week reported more positive affect than those that left their house less often. It is possible that these people experienced more variation, which contributed to positive affect. It is also possible they experienced a greater sense of normality. Future studies are encouraged to further investigate possible mechanisms through which this result unfolds.

Overall, these patterns did not differ substantially between countries. Although some differences did emerge, they were mostly inconsistent across outcomes. Three countries fared worse on two outcomes each: Hong Kong (stress & wellbeing); Turkey (stress & negative affect); and Finland (lower positive affect and higher negative affect)–though participants in Finland also reported higher levels of wellbeing than average. Two countries had more favorable outcomes than the average levels across all countries: Portugal (lower stress and higher wellbeing) and Austria (lower depression and higher wellbeing). The differences observed are likely due to a combination of chance, sampling, nation specific responses to the COVID-19 pandemic, cultural differences, and other factors playing out in the countries (e.g., political unrest [ 38 ]). If replicated, future studies are encouraged to examine possible mechanisms of these outcomes.

This study provides valuable insights on several levels. First, it documents the mental health outcomes across a broad sample during the COVID-19 global pandemic. Second, it informs about the conditions and resilience factors (social support, education, and psychological flexibility) and risk factors (loss of income and inability to get basic supplies) that affect mental health outcomes. Third, these factors can be used in future public health responses are being made, including those that require large scale lockdowns or quarantines. That is, public health officials should direct resources to identifying and supporting people with poor social support, income loss, and potentially lower levels of education and provide a strategy to mitigate special risks in these subpopulations. The importance of social support needs to be made clear to the public and to the degree possible mechanisms that can contribute to social support should be supported. Further, psychological flexibility is a trainable set of skills that has repeatedly been shown to ameliorate suffering [ 22 , 39 ]; and can be widely distributed with modern technological intervention tools such as digital, internet, or virtual means [ 40 ]. We do not claim, however, that psychological flexibility is the only factor that can be used for interventions. Instead, it is a recognized transdiagnostic factor assessed in this study and one that is feasible to be targeted and modified by interventions and prevention [ 41 – 43 ].

This study is limited by several important factors. First, the results are based on cross sectional analysis and correlations. As such, causation cannot be inferred and any delayed impact of the pandemic and lockdown on peoples’ mental health was not captured. Second, all results of this survey were obtained via self-report questionnaires, which can be subject to retrospective response bias. Third, although the sample was large and based on varied recruitment sources, it was not representative of the population and undersampled people who suffered most from the pandemic (i.e., front line health care professionals, people in intensive care, etc.) or people without internet access, etc. Finally, the country-specific incidence rates and lockdown measures differed across countries. These were not assessed, but future studies are encouraged to investigate how such factors impact mental health outcomes.

These limitations notwithstanding, based on nearly 10,000 international participants, this study found that approximately 10% of the population was languishing during or shortly after the lockdown period. These finding have implications for public health initiatives. First, officials are urged to attend to, find, and target people who have little social support and/ or whose finances have worsened as a result of the measures. Second, public health interventions are further urged to target psychological processes such as psychological flexibility in general to potentially help buffer other risk factors for mental health. Likewise, availability of social support and information about where to get support and remain connected are needed. These recommendations should become part of public health initiatives designed to promote mental health in general, and should equally be considered when lockdowns or physical distancing are prescribed during a pandemic.

Supporting information

S1 table. list of all countries included in the data set..

https://doi.org/10.1371/journal.pone.0244809.s001

S2 Table. Geodemographic predictors for Perceived Stress Scale.

https://doi.org/10.1371/journal.pone.0244809.s002

S3 Table. Geodemographic predictors for MSBS–depression.

https://doi.org/10.1371/journal.pone.0244809.s003

S4 Table. Geodemographic predictors for PANAS positive.

https://doi.org/10.1371/journal.pone.0244809.s004

S5 Table. Geodemographic predictors for PANAS negative.

https://doi.org/10.1371/journal.pone.0244809.s005

S6 Table. Geodemographic predictors for MHCSF—mental health continuum.

https://doi.org/10.1371/journal.pone.0244809.s006

S1 Appendix. Participation flowchart.

https://doi.org/10.1371/journal.pone.0244809.s007

Acknowledgments

We wish to thank the following people for their work in helping to implement the study: Spyros Demosthenous, Christiana Karashali, Diamanto Rovania (University of Cyprus); Maria Antoniade (European University of Cyprus); Ioanna Menoikou (Cyprus University of Technology); Elias Ioannou (University of Nicosia); Sonja Borner, Victoria Firsching-Block, Alexander Fenn (University of Basel); Cristīne Šneidere, Ingrīda Trups-Kalne, Lolita Vansovica, Sandra Feldmane, (Riga Stradiņš University); David Nilsson (Lund University); Miguel A. Segura-Vargas (Fundación Universitaria Konrad Lorenz); Claudia Lenuţa Rus, Catalina Otoiu, Cristina Vajaean (Babes-Bolyai University). We further wish to thank Fabio Coviello and Sonja Borner (University of Basel) for their help in preparing the manuscript.

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• Published: 10 April 2024

Post-traumatic stress disorder during the Covid-19 pandemic: a national, population-representative, longitudinal study of U.S. adults

• Salma M. Abdalla   ORCID: orcid.org/0000-0001-5474-4521 1 ,
• Catherine K. Ettman 2 ,
• Samuel B. Rosenberg 1 ,
• Ruochen Wang 1 ,
• Gregory H. Cohen 1 &
• Sandro Galea 1  

npj Mental Health Research volume  3 , Article number:  20 ( 2024 ) Cite this article

Metrics details

• Human behaviour
• Psychiatric disorders

Substantial literature documents the impact of mass traumatic events on post-traumatic stress disorder (PTSD) in populations. However, the trajectory of PTSD in the US population during the pandemic and the association between assets, Covid-19 related stressors, and PTSD over time remains unclear. The Covid-19 and Life Stressors Impact on Mental Health and Well-Being (CLIMB) is a nationally representative, longitudinal panel of US adults in Spring 2020 ( N  = 1270), 2021 ( N  = 1182), and 2022 ( N  = 1091). Using the four-item PC-PTSD-4, we assessed the prevalence of probable PTSD in the US population over three years. Using generalized estimating equations (GEE) and logistic regression at each wave, we estimated associations of demographics, assets, and stressors with probable PTSD. Here we report that the overall prevalence of PTSD decreases from 22.2% in 2020 to 16.8% in 2022 ( p  = 0.02). Persons with household incomes below $20,000 report higher prevalence of probable PTSD compared to other income groups. The GEE model shows higher odds of probable PTSD among persons with household incomes below $20,000 (OR = 2.17 (95%CI: 1.35,3.50)) relative to $75,000 or more; and high stressor scores (OR = 2.33 (95%CI: 1.72,3.15)) compared to low stressor scores. High stressor scores are associated with higher odds of probable PTSD in 2020 (OR = 2.69 (95%CI: 1.56,4.66)), 2021 (OR = 4.58 (95%CI: 2.52,8.30)), and 2022 (OR = 3.89 (95%CI: 2.05,7.38)) compared to low stressor scores. This analysis highlights the pandemic’s prolonged influence on population mental health, particularly among persons with fewer economic assets and those experiencing more pandemic-related stressors. Reducing mental health disparities requires interventions to address inequities.

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Introduction

The Covid-19 pandemic, similar to other mass traumatic events, has been associated with a substantial increase in adverse mental health indicators. Several studies have documented worsening mental health in the United States and globally, including a rise in post-traumatic stress disorder (PTSD) 1 , 2 , 3 . This rise in PTSD can be attributed to the pandemic’s role as a mass traumatic event 3 , 4 , 5 , 6 . This is consistent with literature from other mass traumatic events such as natural disasters and other disease outbreaks 5 , 7 , 8 , 9 , 10 , 11 , 12 .

Previous work has illustrated the role social and economic stressors play in the rise of adverse mental health outcomes during the pandemic, including PTSD 3 , 6 , 13 , 14 , 15 . This is consistent with research following other mass traumatic events. Experiencing event-related stressors—such as deaths of loved ones or friends, displacement, property damage, and financial problems—has been associated with greater PTSD risk 9 , 10 , 16 , 17 , 18 . However, evidence of the relation between experiencing specific pandemic-related stressors and PTSD remains limited in the literature.

There is ample research on the long term mental health consequences of experiencing mass traumatic events, including PTSD, well beyond the initial event 4 , 5 , 19 , 20 , 21 , 22 , 23 . Studies assessing PTSD following the Covid-19 pandemic have generally been cross-sectional or have restricted the longitudinal observation period to under a year 24 . Relatively few longitudinal studies assessed PTSD one year or longer after the start of the pandemic or assessed the long term association between exposure to pandemic-related stressors and PTSD 25 , 26 , 27 , 28 .

We aim to address this gap in the literature by documenting the course of probable PTSD following the pandemic and the associations between exposure to social and economic stressors and PTSD over time using a nationally representative longitudinal cohort. Specifically, this paper aims to (1) estimate probable PTSD prevalence three years into the Covid-19 pandemic; (2) evaluate the association between experiencing social and economic stressors and PTSD; and (3) assess how assets relate to probable PTSD throughout the pandemic.

Study population and Sample size

Using a random sample of adult participants in the AmeriSpeak Panel, we collected nationally representative data for the Covid-19 and Life Stressors Impact on Mental Health and Well-Being Study (CLIMB). Additional details on the recruiting process are available in a previous publication 6 . Online and telephone surveys occurred near the beginning of the Covid-19 pandemic from March 31, 2020 to April 13, 2020 (Time 1, T1), one year into the Covid-19 pandemic from March 23, 2021 to April 19, 2021 (Time 2, T2), and two years into the Covid-19 pandemic from March 22, 2022 to April 18, 2022 (Time 3, T3).

We calculated two post-stratification weights: one for participants who completed at least two waves and one for each wave. The participation frequency and completion rate are available in a previous publication 6 . The institutional review boards of the National Opinion Research Center (NORC) at Chicago University and Boston University Medical Campus (H-39986) approved the study. NORC obtained written consent from study participants when they first enrolled in the AmeriSpeak Panel.

To maximize sample size and accuracy of estimations, we used complete samples for participants who responded to T1 ( N  = 1270), T2 ( N  = 1182), or T3 ( N  = 1091). For the cross-sectional analyses, we removed participants from T1 who did not complete at least two waves ( N  = 199) or were missing a PTSD score from T1 ( N  = 13), T2 ( N  = 15), or T3 ( N  = 12). Participants with only one remaining PTSD score were also removed from T1 ( N  = 9) and T2 ( N  = 3).

Demographic characteristics and other key variables

Gender was defined as a binary variable: man or woman. Age was defined as a categorical variable: 18–39, 40–59, or 60 years or older. Ethnicity was collapsed into a mutually exclusive categorical variable: non-Hispanic Asian, non-Hispanic Black, Hispanic, Multiple or other, or non-Hispanic white, ascertained from participant self-reporting. Educational attainment was defined as a binary variable: less than a college degree or college degree or more.

We measured assets and household size. In this analysis, assets refer to household income, household savings, debts, and home ownership. Household income was defined as a categorical variable: $19,999 or less; $20,000–$44,999; $45,000–$74,999; and $75,000 or more. Household savings was defined as a binary variable: $19,999 or less or $20,000 or greater. Home ownership was defined as a categorical variable: Own, Rent, or Other. Debt was defined as a categorical variable, consisting of all household debts (college loans, mortgage, etc.): no debt; $9999 or less; and $10,000 or more. Household size was a continuous variable that included all persons living in the home, ranging from one to seven or more.

History of Covid-19 infection was defined in response to the question at T1 and T2, “Has a doctor or other health professional ever told you that you had coronavirus or COVID-19?” and the question at T3, “Have you ever tested positive for coronavirus or COVID-19?” Covid-19 vaccine status was measured at T2 and T3 by asking participants, “Have you received at least one shot of the COVID-19 vaccine?”

Pandemic related stressors

Participants were asked if they had ever experienced a series of enumerated stressors due to Covid-19 at T1 and if they had experienced Covid-19 induced stressors in the past 12 months at T2 and T3. We measured 15 stressors based on previous studies conducted after traumatic events and as previously published 3 , 13 . Stressor counts were divided into three categories based on terciles at T1 and T2: low stressor count (zero to three stressors), medium stressor count (four to five stressors), and high stressor count (six or more stressors). The T2 and T3 survey waves had additional stressors that were not in T1, which we used for developing Figs. 4A , B and 5 . The additional stressors we based on our evolving knowledge of the consequences of the pandemic. These stressors included: being forced to leave campus, experiencing a housing eviction or losing housing, not having enough food to eat, losing health insurance, and experiencing divorce or separation.

Post-traumatic stress disorder symptoms

Participants completed the four-item PTSD checklist (PC-PTSD-4) to assess the presence of probable PTSD. Probable PTSD was defined as a score of 3 or greater 29 . We also analyzed each PTSD symptom separately for each measured stressor at T2 and T3. While we did not assess past traumatic events, we anchored the survey in the context of the Covid-19 pandemic as a mass traumatic event. For example, we prefaced the PC-PTSD-4 questions with the following format: “Has the coronavirus or COVID-19 outbreak been so frightening, horrible, or upsetting that you had nightmares about it or thought about it when you did not want to?”

Statistical analysis

To adjust for sample selection factors, we weighted all analyses using multiple post-stratification survey weights: one at each time point and one for participants who completed at least two time points. We used either the weights for one time point or the weights for at least two time points depending on the type of analysis. First, we summed stressors and created terciles of low, medium, and high stressor sums. Second, we stratified probable PTSD prevalence by demographic characteristics at T1, T2, and T3, comparing the prevalence using a two-tailed chi-square test and two-sample t-test. Third, to understand how economic circumstances at the beginning of the pandemic shaped the course of PTSD, we anchored household income and household savings to T1 and estimated probable PTSD prevalence at T1, T2, and T3 by household income and household savings at T1.

Fourth, we calculated the overall prevalence of probable PTSD for the sum of all stressors and by each stressor at T2 and T3. Fifth, we estimated the adjusted odds of probable PTSD across time using general estimating equations (GEE) to account for repeated measures, controlling for gender, age, ethnicity, educational attainment, income, savings, home ownership, household size, history of Covid-19 infection, Covid-19 vaccine status (T2 and T3 only), and stressor category. Sixth, using logistic regression, we estimated the adjusted odds of probable PTSD at T1, T2, and T3 in each time-specific sample.

We conducted analyses in R v4.2.1, complementing the process with the packages data.table, here, survey, haven, gt, gtsummary, tidyverse, geepack, geeasy, geeM, srvyr, convey, paletteer, ggthemes, pacman, and MESS 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 .

Sample demographics

Participants in the cross-sectional samples numbered 1252 in T1, 1165 in T2, and 1081 in T3, consisting of responders who had a PTSD score for at least two waves. Although we presented the weighted sample of responders at T1 in a separate paper 3 , these criteria restricted the sample, resulting in different demographic distributions. In the weighted sample of responders at T1 ( N  = 1252), over half were women (51.0%), 35.2% were non-white, 35.7% had a college degree or more, 69.1% had a household income below $75,000, 58.0% had less than $20,000 in household savings, and 40.9% had $10,000 or more in household debt. In the weighted sample of responders at T2 ( N  = 1165), over half were women (51.7%), 37.2% were non-white, a third had a college degree or more (35.2%), 69.4% had a household income below $75,000, over half had less than $20,000 in household savings (52.8%), 42.4% had $10,000 or more in household debt, 11.1% had had a previous Covid-19 infection, and less than half had had a Covid-19 vaccine (42.9%). In the weighted sample of responders at T3 ( N  = 1081), over half were women (52.1%), 37.0% were non-white, a third had a college degree or more (34.6%), two-thirds had a household income below $75,000 (66.0%), over half had less than $20,000 in household savings (52.4%), 37.3% had $10,000 or more in household debt, a third had had a Covid-19 infection (33.2%), and 81.1% had had a Covid-19 vaccine. The longitudinal analytic sample included only participants who had at least one response to all variables included in the model, with the final sample consisting of 1159 participants from T1, 1070 from T2, and 954 from T3.

Responders at T2 ( N  = 1165) and non-responders at T2 ( N  = 93) were demographically comparable at T1, except for ethnicity and household savings. Compared to responders at T2, more non-responders were non-white, and more non-responders had under $20,000 in household savings. (Supplementary Table 1 ). Responders at T3 ( N  = 1081) and non-responders at T3 ( N  = 177) were demographically comparable at T1, except for age, ethnicity, debt, and household size. More non-responders were 18–39 years, more non-responders were non-white, and non-responders had larger household sizes compared to responders at T3 (Supplementary Table 2 ).

Probable PTSD prevalence over time

Table 1 shows the frequency and weighted percentage of the sample population with probable PTSD at T1, T2, and T3. Supplementary Table 3 provides the distribution of PTSD scores by wave. Probable PTSD prevalence decreased in each subsequent year compared to the previous year. The difference between probable PTSD prevalence at T1 and T3 was statistically significant. A higher prevalence of probable PTSD occurred in women compared to men, with statistical significance at T1 and T2. The youngest age group had the highest prevalence of probable PTSD; this prevalence decreased with older age, with statistical significance at T1. Across each wave, Hispanic participants had the highest prevalence of probable PTSD, followed by white participants at T1 and by Black participants at T2, and by multiple or other ethnicity participants at T3.

Participants with less than a college degree had a higher prevalence of probable PTSD than participants with a college degree or more. Probable PTSD prevalence was higher in participants with a history of Covid-19 infection. Nearly a quarter of participants who had received at least one Covid-19 vaccine at T2 had probable PTSD, compared to 20.1% of participants who had not received the Covid-19 vaccine. At T3, having the Covid-19 vaccine was associated with a higher prevalence of probable PTSD, reaching statistical significance (Table 1 ).

Assets and probable PTSD prevalence

The group with the lowest household income (≤$19,999) had the highest prevalence at T1 and T3. Prevalence of probable PTSD generally decreased with increasing income, except for T2, when the $20,000–$44,999 group had the highest prevalence of probable PTSD. There was a statistically significant association between household income and probable PTSD. Figure 1 shows the probable PTSD prevalence at each time point, stratified by household income level anchored to T1. Participants in the lowest household income group at T1 had the highest prevalence of probable PTSD at any time point, and each increasing income level had a lower prevalence of probable PTSD at T1 and T2. Supplementary Fig. 1 includes error bars.

Household income data anchored to T1. Respondents have same household income in T2 and T3 as they did in T1. Household income in $USD. Data weighted. T1 weights used for T1 estimates; T2 weights used for T2 estimates; T3 weights used for T3 estimates Probable PTSD defined by Primary Care PTSD Screen for DSM-5 (PC-PTSD-4) score of 3 or greater. Data source: COVID-19 and Life Stressors Impact on Mental Health and Well-being study. Time 1 collected from March 31, 2020, to April 13, 2020. Time 2 collected from March 23, 2021, to April 19, 2021. Time 3 collected from March 22, 2022, to April 18, 2022. At T1, 26 respondents had missing or unknown household income. At T2, 31 respondents had missing or unknown household income. At T3, 27 respondents had missing or unknown household income.

Over a quarter of the group with $19,999 or less in household savings had probable PTSD at T1 and T2, decreasing to under a quarter at T3. In the group with more than $20,000 in household savings, 16.5% had probable PTSD at T1, 16.4% at T2, and 11.0% at T3. The relation between household savings and probable PTSD was statistically significant. Figure 2 shows the probable PTSD prevalence at each time point, stratified by household savings level anchored to T1. Participants with $19,999 or less in household savings at T1 had a higher prevalence of probable PTSD than participants with more in household savings at any time point. Supplementary Fig. 2 includes error bars.

Household savings data anchored to T1. Respondents have same household savings in T2 and T3 as they did in T1. Household income in $USD. Data weighted. T1 weights used for T1 estimates; T2 weights used for T2 estimates; T3 weights used for T3 estimates. Probable PTSD defined by Primary Care PTSD Screen for DSM-5 (PC-PTSD-4) score of 3 or greater. Data source: COVID-19 and Life Stressors Impact on Mental Health and Well-being study. Time 1 collected from March 31, 2020, to April 13, 2020. Time 2 collected from March 23, 2021, to April 19, 2021. Time 3 collected from March 22, 2022, to April 18, 2022. At T1, 32 respondents had missing or unknown household savings. At T2, 38 respondents had missing or unknown household savings. At T3, 33 respondents had missing or unknown household savings.

Over a quarter of the group with $10,000 or more in household debt had probable PTSD at T1, decreasing to under a fifth at T3. The group with $9999 or less in household debt paralleled this trend, decreasing from 23.1% at T1 to 16.2% at T3. Participants with no debt had the lowest probable PTSD at every time point, reaching as low as 13.6% at T1, increasing to 15.8% at T2, and decreasing to 14.7% at T3. Figure 3 shows the probable PTSD prevalence at each time point. Supplementary Fig. 3 includes error bars.

Household debt data anchored to T1. Respondents have the same household debt as they did in T1. Household debt in $USD. Data weighted. T1 weights used for T1 estimates; T2 weights used for T2 estimates; T3 weights used for T3 estimates. Probable PTSD defined by Primary Care PTSD Screen for DSM-5 (PC-PTSD-4) score of 3 or greater. Data source: COVID-19 and Life Stressors Impact on Mental Health and Well-Being study. Time 1 collected from March 31, 2020, to April 13, 2020. Time 2 collected from March 23, 2021, to April 19, 2021. Time 3 collected from March 22, 2022, to April 18, 2022. At T1, 21 respondents had missing or unknown household debt. At T2, 27 respondents had missing or unknown household debt. At T3, 24 respondents had missing or unknown household debt.

More than a fifth of renters had probable PTSD, with more having probable PTSD at each time point compared to homeowners. Participants in the other (non-home owners or renters) category had the highest rate of probable PTSD. There was a statistically significant relation between home ownership type and probable PTSD at T3. The mean household size of participants with probable PTSD decreased in each subsequent year. At T1, the mean household size was larger in participants with probable PTSD compared to the mean household size in participants without probable PTSD (Table 1 ).

Pandemic-related stressors and probable PTSD

At each time point, approximately a third of participants with a high stressor score had probable PTSD. Supplementary Table 4 provides the distribution of stressor scores for each wave. Approximately a fifth of participants with a medium number of stressors had probable PTSD. Around a tenth of participants who had a low number of stressors had probable PTSD. The association between stressor category and probable PTSD was statistically significant. Figure 4A shows the probable PTSD prevalence for each stressor sum at T2. Figure 4B shows the probable PTSD prevalence for each stressor sum at T3. At both timepoints, participants with probable PTSD reported a higher number of stressors than participants without probable PTSD.

A Distribution of Covid-19 Stressors by probable PTSD status at wave T2. B Distribution of Covid-19 Stressors by probable PTSD status at wave T3. A T2 weights used to calculate probable PTSD prevalence. Stressors defined by presence of: having an event canceled due to the Covid-19 pandemic, seeing friends in person less, seeing family in person less, experiencing travel restrictions, experiencing the death of someone close to you due to Covid-19, having family or relationship problems, having challenges finding childcare, feeling alone, not being able to get food due to shortages, not being able to get supplies due to shortages, losing a job, member of household losing a job, having financial problems, and having difficulty paying rent. Probable PTSD defined by Primary Care PTSD Screen for DSM-5 (PC-PTSD-4) score of 3 or greater. Data source: COVID-19 and Life Stressors Impact on Mental Health and Well-being study. Time 3 collected from March 22, 2022, to April 18, 2022. B T3 weights used to calculate probable PTSD prevalence. Stressors defined by presence of: having an event canceled due to the Covid-19 pandemic, seeing friends in person less, seeing family in person less, experiencing travel restrictions, experiencing the death of someone close to you due to Covid-19, having family or relationship problems, having challenges finding childcare, feeling alone, not being able to get food due to shortages, not being able to get supplies due to shortages, losing a job, member of household losing a job, having financial problems, and having difficulty paying rent. Probable PTSD defined by Primary Care PTSD Screen for DSM-5 (PC-PTSD-4) score of 3 or greater. Data source: COVID-19 and Life Stressors Impact on Mental Health and Well-being study. Time 3 collected from March 22, 2022, to April 18, 2022.

Figure 5 shows the prevalence of probable PTSD for persons experiencing and not experiencing each stressor at T2 and T3. The prevalence at T1 was presented in a prior publication 3 . At T2, there was a greater prevalence of probable PTSD in persons who had experienced most stressors, except for having difficulty finding childcare, being forced to leave campus, and working remotely. Over half of persons who experienced not having enough food had probable PTSD (56.4% (95% CI: 37.9%, 73.8%)). Less than a fifth of persons who experienced working remotely had probable PTSD (18.2% (95% CI: 13.4%, 23.7%)). At T3, there was a greater prevalence of probable PTSD in persons who had experienced most stressors, except for event cancellation and difficulty finding childcare. Of persons who lost health insurance, 55.5% had probable PTSD (95% CI: 30.7%, 78.5%). Having difficulty finding childcare had the lowest prevalence, at 15.5% (95% CI: 6.9%, 28.2%). Supplementary Fig. 4a and 4b show the T2 and T3 prevalence of each PC-PTSD-4 symptom for persons experiencing and not experiencing each stressor.

T2 weights used to calculate T2 variables. T3 weights used to calculate T3 variables. Stressors defined by presence of: having an event canceled due to the Covid-19 pandemic, seeing friends in person less, seeing family in person less, experiencing travel restrictions, experiencing the death of someone close to you due to Covid-19, having family or relationship problems, having challenges finding childcare, feeling alone, not being able to get food due to shortages, not being able to get supplies due to shortages, losing a job, member of household losing a job, having financial problems, having difficulty paying rent, being forced to leave campus, experiencing eviction or lost housing, not having enough food to eat, losing health insurance, or experiencing divorce or partner separation. Probable PTSD defined by Primary Care PTSD Screen for DSM-5 (PC-PTSD-4). Data source: COVID-19 and Life Stressors Impact on Mental Health and Well-being study. Time 2 collected from March 23, 2021, to April 19, 2021. Time 3 collected from March 22, 2022, to April 18, 2022. Error bars represent 95% confidence intervals calculated using a Rao-Scott correction.

Odds ratios of probable PTSD by demographic variables, assets, and stressors

Table 2 shows the adjusted odds of probable PTSD at any given timepoint by the demographic variables, assets, and stressors. Income, home ownership, and stressor score were statistically significant in the model. Persons with $19,999 or less in household income had 2.17 times the odds (95% CI: 1.35, 3.50) and persons with $20,000–$44,999 had 1.63 times the odds (95% CI: 1.14, 2.34) of probable PTSD at any given timepoint relative to persons in households earning $75,000 or more. Persons who rented or had other housing had greater odds of probable PTSD compared to those who owned a home. Persons with a medium stressor count (4–5 Covid-19 stressors) had 1.42 times the odds (95% CI: 1.06, 1.89) and persons with a high stressor count (6+ stressors) had 2.33 times the odds (95% CI: 1.72, 3.15) of probable PTSD relative to persons reporting a low stressor count (0–3 stressors).

Table 3 shows the adjusted odds of probable PTSD at T1, T2, and T3 across demographics, assets, and stressors. For each demographic level, the greatest odds of probable PTSD generally occurred at T2. Women had greater odds of probable PTSD at all timepoints relative to men, but the difference in odds decreased in T2 and T3. The 40–59 age category had greater odds than the 18–39 age category at all time points, while the 60+ category had lower odds than the 18–29 age category at all time points. Persons with a history of Covid-19 infection had greater odds of probable PTSD at any time point. Persons with at least one Covid-19 vaccine dose had greater odds of probable PTSD at T2 (1.92 (95% CI: 1.19, 3.11)) and T3 (2.44 (95% CI: 1.29, 4.62)), and these odds were statistically significant.

Persons in the lowest household income group ($19,999 or less) had the greatest odds of probable PTSD at T1 (2.05 (95% CI: 1.11, 3.77)) and T3 (2.39, 95% CI: 1.00, 5.71). At T2, persons in households earning $20,000 to $44,999 had the highest odds of probable PTSD compared to the highest-earning group (3.08 (95% CI: 1.49, 6.38)), and these odds were statistically significant. Persons with $19,999 or less in household savings had greater odds of probable PTSD than persons with $20,000 or more in household savings, at any time point (Table 3 ). Persons with $10,000 or more in household debt had the highest odds of PTSD at T3 (4.18 (95% CI: 1.84, 9.52)).

Compared to persons with a low stressor score, persons with a medium stressor score had greater odds of probable PTSD at T1 (1.64 (95% CI: 0.88, 3.05)), T2 (1.80 (95% CI: 0.94, 3.46)), and T3 (2.22 (95% CI: 1.13, 4.36)), with the odds at T3 reaching statistical significance. Persons with a high stressor score had statistically significantly greater odds of probable PTSD at T1 (2.69 (95% CI: 1.56, 4.66)), T2 (4.58 (95% CI: 2.52, 8.30)), and T3 (3.89 (95% CI: 2.05, 7.38)) relative to persons with a low number of stressors.

This longitudinal representative survey of adults in the United States showed that the population burden of PTSD decreased three years after the start of the pandemic, while still remaining higher than pre-pandemic estimates. Reductions in probable PTSD were strongest for groups with more assets. Moreover, experiencing a greater number of pandemic-related stressors increased the odds of having probable PTSD throughout the pandemic.

Compared to 2020 we found that the prevalence of probable PTSD did not change substantially in 2021 but decreased in 2022. However, the prevalence continued to be higher than pre-pandemic estimates 47 , 48 . Our findings are consistent with analyses from other mass traumatic events 20 , and other studies during the Covid-19 pandemic. Chi et al., showed a decline in PTSD prevalence six months into the pandemic in China, but the prevalence continued to be greater than pre-pandemic levels 49 . Similarly, over a longer term, Benatov et al., reported decreases in PTSD prevalence in four countries between February and June of 2021 50 .

This study found that lack of access to assets, particularly having low income when the pandemic began, was associated with probable PTSD throughout the pandemic. Access to fewer assets—including income, savings, and home ownership—has been associated with a higher burden of mental health indicators, including PTSD, during the pandemic 15 , 51 , 52 , 53 . For example, in a large cross-sectional sample of US adults, Zhu and colleagues reported similar findings for respondents with low income; those earning $75,000 or less had a higher prevalence of PTSD symptoms (24.0%) than those earning $75,000 to $149,999 (21.2%), and those earning $150,000 and over had the lowest prevalence of PTSD symptoms (17.9%) 54 . Our study adds to the literature by showing the association between low income at the beginning of the pandemic and persistent probable PTSD two years later.

Our analysis showed that experiencing Covid-19 stressors was associated with higher likelihood of probable PTSD throughout the pandemic. This is consistent with previous work that showed that experiencing more pandemic-related stressors was associated with a greater likelihood of depression 13 . Conversely, Zaken and colleagues found that when controlling for demographic factors and PTSD history, the association of Covid-19-related stressors was not associated with PTSD 24 . This divergence could potentially be due to differences in the type of stressors examined as well as tools used to assess PTSD.

We also found that experiencing specific social or economic stressor was generally associated with higher PTSD prevalence. Similarly Zaken et al., reported higher post-traumatic stress among participants who reported loss of health insurance coverage, housing-related problems, financial difficulties, and difficulty accessing food or vital supplies 24 . In a longitudinal study by Ochnik et al., worsening economic status was associated with 1.8 times greater odds of PTSD during the pandemic 55 . Our analysis particularly highlighted the association between experiencing food insecurity and greater likelihood of probable PTSD. This is consistent with two studies from Spain and Bangladesh that reported similar results earlier in the pandemic 56 , 57 . Conversely, Liddell et al., reported associations between stressors related to Covid-19 infection but not to social stressors, access to support, or trusting authority and PTSD among refugees in Australia 58 . This variance can potentially be due to the different contexts, which can either heighten or minimize the role of economic and social stressors on mental health.

This analysis is not without limitations. First, as with any large panel study, there is the risk of loss to follow-up. Of the 1470 participants who completed T1, 1002 completed all three waves with a complete PTSD score (68.2%). This was largely due to the strict criteria we implemented on which participants to include in the analysis. Increasing the completion status criterion to two or more waves reduces the loss to follow-up, producing a response rate of 85.6%. Second, the lack of data from participants before the pandemic limits direct comparison to PTSD prevalence prior to the pandemic. Third, participants’ historical diagnoses of probable PTSD were not included in the analysis. However, this analysis does provide a representative, longitudinal, understanding of pandemic stressors and probable PTSD during the pandemic.

Notwithstanding these limitations, these findings demonstrate the long-term impact of the pandemic on population mental health. Over the past three years, experiencing and recovering from PTSD differed by access to assets, with those with fewer economic assets bearing the brunt of the burden. Moreover, exposure to more pandemic-related stressors was associated with higher PTSD prevalence throughout the pandemic. Inequities prior to, and during, the pandemic produced health disparities in population mental health outcomes. Reducing these mental health disparities requires addressing asset inequities as well as take mental health consequences as a consideration when designing efforts to mitigate the spread of disease outbreaks.

Data availability

De-identifiable data are available upon reasonable request made to the corresponding author.

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R code is available upon request.

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CLIMB Time 1 was sponsored by the Rockefeller Foundation-Boston University 3-D Commission. CLIMB Time 2 and 3 were sponsored by the de Beaumont Foundation.

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Abdalla, S.M., Ettman, C.K., Rosenberg, S.B. et al. Post-traumatic stress disorder during the Covid-19 pandemic: a national, population-representative, longitudinal study of U.S. adults. npj Mental Health Res 3 , 20 (2024). https://doi.org/10.1038/s44184-024-00059-w

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From the Association

Statement on Historical Research during COVID-19

AHA Staff | Aug 31, 2020

C OVID-19 is not just altering historians’ everyday life; it has also upended historical research. Although most university and college administrators have issued FAQs, guidelines, and resources that relate to the continuance of laboratory and human subjects research, they have not always addressed the conditions under which historians work or considered how to make accommodations for historical research during the pandemic. Moreover, in assessing productivity at this moment, it is imperative that university administrations recognize the distinctions among disciplines in types of research and to take into account the unusually burdensome tasks of teaching now affecting all instructors.

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• 3 Tampere University Hospital, Tampere, Finland
• 4 Postgraduate Program in Dental Science, School of Dentistry, São Paulo State University (UNESP), Araraquara, Brazil
• 5 Department of Education, Institute of Biosciences, São Paulo State University (UNESP), Rio Claro, Brazil
• 6 William James Center for Research, University Institute of Psychological, Social, and Life Sciences (ISPA), Lisbon, Portugal
• 7 Flu Pedagogy, Nord University, Bodø, Norway

Introduction: The COVID-19 pandemic brought profound societal changes and disruptions, including in the education system, which underwent swift modifications. It presented unique challenges for both professors and students, contributing to an increase in the prevalence of mental health-related symptoms.

Objective: To determine the prevalence of mental health disorders symptoms, coping strategies, and concerns among students (≥18 years) and professors at different times during the COVID-19 pandemic.

Methods: This was an online cross-sectional study (Student: N  = 6,609; Phase 1 = 3,325; Phase 2 = 1,402; Phase 3 = 1,882; Professor: N  = 9,096; Phase 1 = 3,924; Phase 2 = 2,223; Phase 3 = 2,949). Depression, Anxiety, and Stress Scale (DASS-21), Impact of Event Scale-revised (IES-R), and BriefCOPE inventory were used. The probability of presenting the symptoms was calculated by multiple logistic regression and odds ratio (OR).

Results: The prevalence of depression, anxiety, stress, and distress symptoms among students and professors was high (≥59.5% and ≥ 33.5%, respectively). Students, women, and those diagnosed with a mental disorder were more likely to have symptoms or distress. In the face of the pandemic, professors used more adaptive coping strategies than students. Health was the focus of professors’ concerns, while for students, future and labor market uncertainty were concerns derived from the health core.

Conclusion: The results point to the need to strengthen psychosocial support for both professors and students.

1 Introduction

Santos (2020) and Harari (2020) argue that the COVID-19 pandemic has taught us some lessons about human behavior and its impact on the world. The authors ( Harari, 2020 ; Santos, 2020 ) point out that the social isolation and quarantine imposed by the health crisis have raised unprecedented social, economic, political, environmental, physical, and emotional issues. As a result, there have been significant changes in several domains of life that have required us to reshape our ways of living.

In Brazil, with the announcement of the pandemic by the World Health Organization (March 11th, 2020), the Ministry of Health decreed lockdowns in several locations across the country, maintaining only essential services, such as hospitals and food establishments. Among the sectors most impacted by the pandemic was the education system, which initially had its activities suspended. However, with the prolongation of the pandemic, it needed to be quickly reorganized into an emergency distance learning system to ensure continuity ( Sousa and Coimbra, 2020 ; Pinho et al., 2021 ; Telyani et al., 2021 ; Tri Sakti et al., 2022 ).

Both professors and students had to adapt to technological and digital resources to make the teaching-learning process viable. This transition demanded proactivity and creativity in implementing synchronous and asynchronous activities. However, there were immediate consequences, such as the expansion of the working hours of professors, the precariousness of working conditions adapted in households, increased spending on work equipment, and a general safety ( Bernardo et al., 2020 ; Azzi et al., 2022 ; Weibenfels et al., 2022 ). Although these consequences were initially focused on the configurations of teaching during the pandemic ( Bernardo et al., 2020 ; Azzi et al., 2022 ; Weibenfels et al., 2022 ), they can be easily extended to students as well.

The surveys conducted with professors ( Bernardo et al., 2020 ; Ozamiz-Etxebarria et al., 2021 ; Pinho et al., 2021 ) show that, regardless of their teaching level and sector (elementary, secondary, or higher education, public or private), many of them encountered an unfamiliar universe, not only in terms of using technology to deliver instruction but also in terms of establishing connections with students and peers in non-face-to-face spaces. Being outside the classroom environment and having family obligations that intersected with course requirements were aggravating elements of the learning process for both professors and students. For students, this experience was perhaps even more remarkable due to the chaotic scenario characterized by a lack of signs of new opportunities and future professional possibilities and chronic inequalities that were constantly and rapidly changing ( Kivunja, 2015 ; Harari, 2018 ). The limited skills and behavioral repertoire that younger people have to cope with so many challenges indicate the complexity of adapting their routine to the pandemic reality ( Campos et al., 2020 ).

In the dynamic of a teaching-learning process where students are the protagonists, the responsibility of the professor extends beyond the mere transmission of information and the construction of knowledge. It should also involve developing the active participation of students in their learning process, giving them autonomy and freedom to carry out their own construction so that learning becomes significant for them. This, in turn, enables the building of educational spaces and relationships in a historical and multicultural context ( Freire, 1996 ). However, the complexity of teaching and the challenges for the unfolding of student protagonism in this unfavorable scenario of the pandemic, especially for those preparing for and approaching the labor market, can lead to overload and physical and mental illness.

In previous studies, a high prevalence of depression, anxiety, stress, and subjective distress symptoms was found among university students ( Chang et al., 2021 ; Li et al., 2021 ; Wang et al., 2021 ; Campos et al., 2021a ) and professors ( Ozamiz-Etxebarria et al., 2021 ; Silva et al., 2021 ). Li et al. (2021) and Silva et al. (2021) indicate that after the onset of the COVID-19 pandemic, this prevalence increased. Some studies also point to a worrisome prevalence of burnout among students ( Azzi et al., 2022 ; Salmela-Aro et al., 2022 ) and professors ( Pressley, 2021 ; Weibenfels et al., 2022 ) given the overload caused not only by the health crisis but also by the rapid and massive transformation of the educational process during COVID-19.

Education in times of pandemic therefore becomes a challenging task, and as we witness the renewal of teaching and learning processes in this scenario, we must have a supportive look at how professors and students have experienced, how they have suffered, how they have resigned, and how these experiences have finally revealed fundamental questions about the life and mental health in this context. We cannot but emphasize that the pandemic severely shook the journey of students in the final year of their program and on their way to professional life, as they were not on school campuses and thus felt even more fragile in their professional identity formation, which in the context of the pandemic seems so far removed from concrete reality.

Thus, this study aimed to gather information on the mental health of Brazilian professors and students (over 18 years old) during the COVID-19 pandemic using a large national sample. Self-reported information was collected to identify the prevalence of mental health disorder symptoms, coping strategies, and main concerns at different times during the pandemic. To the best of our knowledge, this is the first study conducted with a large sample of Brazilian professors and students during different periods of the pandemic, providing relevant information to understand the educational scenario during the pandemic from the perspective of its actors. The evidence presented may also be useful for developing programs and actions aimed at promoting mental health and well-being in the educational environment.

Despite numerous studies conducted during the COVID-19 pandemic, to the best of our knowledge, no research has provided data on coping mechanisms and symptoms across multiple stages of the pandemic or simultaneously collected data from both teachers and students. Thus, the present study is also justified by the scarcity of such information in existing literature. This information could deepen understanding of global transformations in education and their impact on the mental health of teachers and students. This knowledge could better equip practitioners and researchers to develop strategies to handle future crises and support the educational population.

Three main theoretical frameworks were used in the conduction of the present study: one for assessing and interpreting coping strategies; another for identifying symptoms of depression, anxiety, and stress; and a third for recognizing subjective distress in response to the pandemic. To assess coping strategies, the cognitive and behavioral perspective described by Carver et al. (1989) was applied in the present study. These authors developed a model based on the study of Folkman and Lazarus (1980) and on the studies of their own research group, which presented a behavioral model of self-regulation ( Carver and Scheier, 1981 , 1983 , 1985 ; Scheier and Carver, 1988 ). Folkman and Lazarus (1980) proposed a model that divides coping into two functional categories: 1. problem-focused coping and 2. emotion-focused coping. Additionally, it is considered that the coping strategy employed, regardless of its functional category, should not be inherently labeled as good or bad, adaptive or maladaptive ( Folkman and Lazarus, 1980 ; Carver et al., 1989 ). Understanding both the nature of the stressor and the individual and social context involved is necessary. From this perspective, coping refers to cognitive and behavioral efforts, which are deliberate actions individuals undertake to deal with specific demands.

Regarding symptoms of depression, anxiety, and stress, the theoretical model employed in the present study was the one that considers a clinical overlap among these concepts ( Watson et al., 1995 ). This proposal is grounded in the tripartite model, in which symptoms of anxiety and depression are grouped into three basic structures: 1. the presence of negative affects, such as depressed mood, insomnia, discomfort, and irritability; 2. factors representing specific symptoms for depression (anhedonia and absence of positive affect); and 3. specific symptoms of anxiety, including somatic tension and hyperactivity ( Watson et al., 1995 ).

For identifying subjective distress, we used a psychometric scale ( Caiuby et al., 2012 ) developed based on the criteria outlined in the third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III) ( American Psychiatric Association, 1980 ). We clarify that, when conducting the present study, we did not find other simple and self-administered scales for assessing subjective distress that had been developed following the most current edition of DSM (5th ed., DSM-5) ( American Psychiatric Association, 2013 ). Furthermore, given that the present study was conducted online, we understood that using clinical criteria without a clinical assessment would not be feasible. Therefore, the framework adopted for subjective distress was based on the DSM-III ( American Psychiatric Association, 1980 ).

2.1 Study design and participants

This cross-sectional study used online data from a larger project approved by the National Commission for Ethics in Research of the Ministry of Health (CONEP). The larger project is a national survey that has collected data at three-time points, 6 months apart since the beginning of the pandemic, using Google Form or Lime Survey platforms. 1 The link to the survey was sent by email, WhatsApp, or social networks, and remained accessible for about 40 days. The initial contact was made through publicly accessible information on websites of Brazilian higher education institutions (public and private) using non-probability sampling, and the participants were asked to distribute the link to work and personal contacts (snowball technique).

The inclusion criteria were age ≥ 18 years and being a student or professor. In Brazil, students who are 18 years old may be attending the final years of high school/technical school or the first years of undergraduate studies. However, the present study did not differentiate between these levels, as our interest was solely in identifying the participants’ “professional category,” which in this case, was either student or professor. As educational level varies according to age, we chose to control for the effect of age in our statistical analyses rather than specifying educational categories. Information on the teaching level (elementary, high school, or higher education), the type of institution (public or private) of professors, and the education level of the students was also not available. Despite this being a limitation of the study, we understand that its conduction may provide information and trigger relevant reflections that could serve as a starting point for the development of future studies focused on assessing the mental health of these individuals in the peri and post-pandemic context. A total of 12,196, 6,261, and 7,977 people participated in phases 1, 2, and 3, respectively.

2.2 Sample characterization and study variables

Information on age (years), gender (man, woman, non-binary), Brazil macro-region, monthly family income (by income range, in Brazilian reals), pre-existing diagnosis of mental disorder before the pandemic, perceived safety toward the pandemic (very unsafe, unsafe, safe, very safe), and mental health alterations since the beginning of the pandemic (no, yes) was collected. The dependent variables were symptoms of depression, anxiety, stress, subjective distress, and the coping strategies used by the participants. Additionally, participants were asked to provide three open-ended responses to the question: “What are your top 3 concerns at the moment?”

2.3 Sample size calculation

The minimum sample size was calculated based on the number of items of the longest scale (28 items and 14 correlated factors), the number of parameters to be estimated (119), and 5 to 10 participants per parameter. This resulted in a minimum sample size of 595 to 1,190 participants. This sample size was calculated to ensure that the analytical strategies could be conducted, including the verification of the factorial validity of the scales in the samples.

2.4 Measuring scales

The Portuguese version of the Depression, Anxiety and Stress Scale (DASS-21) ( Martins et al., 2019 ), the Impact of Event Scale-revised (IES-R) ( Caiuby et al., 2012 ), and the BriefCOPE Inventory ( Maroco et al., 2014 ) were used in the study.

The DASS-21 has 21 items distributed in 3 factors (Factor/item examples - Depression: “ I felt I wasn’t worth much as a person ,” Anxiety: “ I felt scared without any good reason ” and Stress: “ I felt that I was using a lot of nervous energy ”) and a 4-point Likert-type response scale. The scores of each item are added and multiplied by two. The participants were then grouped according to the degree of involvement, following the proposal of Lovibond and Lovibond (1995) (Depression: Normal - 0 to 9, Mild - 10 to 13, Moderate - 14 to 20, Severe - 21 to 27, and Extremely severe ≥28; Anxiety: Normal - 0 to 7, Mild - 8 to 9, Moderate - 10 to 14, Severe - 15 to 19, and Extremely severe ≥20; Stress: Normal - 0 to 14, Mild - 15 to 18, Moderate - 19 to 25, Severe - 26 to 33, and Extremely severe ≥34).

The IES-R has 22 items distributed in 3 factors (Factor/item examples – Avoidance: “I avoid letting myself get upset when I think about it or I am reminded of it,” Intrusion: “Other things keep making me think about it,” and Hyperarousal: “Reminders of it cause me to have physical reactions, such as sweating, trouble breathing, nausea, or a pounding heart” ), but a general score for subjective distress can be obtained by the sum of the responses (Normal - 0 to 23, Mild - 24 to 32, Moderate - 33 to 36, Severe - ≥37) ( Wang et al., 2020 ). The items have a 5-point Likert-type response scale.

The BriefCOPE has 28 items arranged in 14 factors (Factor/item examples - Active Coping – AC: “I’ve been taking action to try to make the situation better,” Planning – PL: “I’ve been thinking hard about what steps to take,” Instrumental Support – IS: “I’ve been getting help andadvice from other people,” Emotional Support – ES: “I’ve been getting emotional support from others,” Religion – RE: “I’ve been praying or meditating,” Positive Reinterpretation – PR: “I’ve been looking for something good in what is happening,” Self-Blame – SB: “I’ve been criticizing myself,” Acceptance – AT: “I’ve been learning to live with it,” Venting of Emotions – VE: “I’ve been expressing my negative feelings,” Denial – DN: “I’ve been saying to myself “this is not real,” Self-Distraction – SD: “I’ve been turning to work or other activities to take my mind off things,” Behavioral Disengagement – BD: “I’ve been , Substance Use – SU: “I’ve been using alcohol or other drugs to make myself feel better,” and Humor – HU: “I’ve been making jokes about it” ) ( Carver, 1997 ). The scale is answered on a 5-point scale ( Maroco et al., 2014 ) and the participants were grouped considering the average score of each factor into usual strategy (≥3) and non-usual strategy (<3).

2.5 Data validity and reliability

The factorial validity of the data was estimated by confirmatory strategy with a robust estimation of weighted least squares means and variances adjusted (WLSMV). The model fit to the data was evaluated using the following indices: Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA) with a 90% confidence interval ( Marôco, 2021 ; Kline, 2023 ). Data reliability was analyzed to verify the consistency of the obtained information, and it was estimated using the Ordinal Coefficient alpha (α). Values of α ≥ 0.70 were considered indicative of adequate reliability. The analyses were conducted in the R program ( R Core Team, 2022 ) using the “ lavaan ” ( Rosseel, 2012 ) and “ semTools ” ( Jorgensen et al., 2022 ) packages.

The factorial validity of the data was confirmed for each sample and phase of data collection separately (Student – DASS-21: CFI = 0.974–0.976, TLI = 0.971–0.973, RMSEA = 0.059–0.064; BriefCOPE: CFI = 0.949–0.985, TLI = 0.926–0.978, RMSEA = 0.050–0.077; IES-R: CFI = 0.951–0.966, TLI = 0.944–0.961, RMSEA = 0.067–0.080; Professor – DASS-21: CFI = 0.971–0.982, TLI = 0.967–0.979, RMSEA = 0.058–0.066; BriefCOPE: CFI = 0.964–0.984, TLI = 0.948–0.977, RMSEA = 0.064–0.082; IES-R: CFI = 0.968–0.976, TLI = 0.963–0.973, RMSEA = 0.062–0.068). Reliability was also confirmed (Student – DASS-21: α  = 0.86–0.94; BriefCOPE: α  = 0.70–0.97; IES-R: α  = 0.85–0.92; Professor – DASS-21: α  = 0.88–0.95; BriefCOPE: α  = 0.70–0.96; IES-R: α  = 0.88–0.94).

2.6 Similarity analysis

The concerns expressed by professors and students underwent qualitative analysis using similarity analysis, a graph-theoretic method for determining the relationships between the reported concerns of each group about the pandemic. This analysis was conducted for the general sample of each occupational category, without separating the different phases of data collection. With this analysis, it was possible to identify the occurrences/co-occurrences and narrow down the relations between the pandemic-related concerns mentioned by the participants. A static Fruchterman Reingold graph was created to present the results using the Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires - Iramuteq software (version 0.7 alpha 2) ( Ratinaud, 2008/2023 ).

2.7 Statistical analysis

The prevalence of depression, anxiety, stress, and subjective distress symptoms was calculated as a point value with a 95% confidence interval (95%CI) and compared between the data collection phases (within each occupational group) using the z test ( α =5%). The prevalence of usual (mean ≥ 3) coping strategies was also estimated and compared in the same way as described previously.

For each outcome (depression, anxiety, stress, and subjective distress), a multiple logistic regression model was developed: 0 = normal; 1 = mild, moderate, severe, or extremely severe distress taking into account gender [reference category (ref): man], presence/absence of a previous diagnosis of a mental disorder (ref: absent), occupational group [0 = professor (ref); 1 = student], and age. This analysis was performed separately for each phase of data collection. The odds ratio was estimated by point and 95%CI.

2.8 Ethical aspects

Participants voluntarily accessed the link to the survey and signed the informed consent form. The study followed the ethical guidelines of the National Health Council Decision 466/12 and 510/2016 and the guidelines of resolution No. 1/2021-CONEP/SECNS/MS on research in a virtual environment. This study was approved by the National Research Ethics Committee of the Ministry of Health (CONEP) (CAAE 30604220.4.0000.0008).

A total of 6,609 students (Phase 1 = 3,325; Phase 2 = 1,402; Phase 3 = 1,882) and 9,096 professors (Phase 1 = 3,924; Phase 2 = 2,223; Phase 3 = 2,949) participated in the study. Table 1 shows the characteristics of the sample. Of note is the higher prevalence of a previous diagnosis of a mental disorder reported by students compared to professors. There was also a significant difference in the prevalence of mental health changes reported by the two occupational groups since the onset of the pandemic, with students being more affected.

Table 1 . Sample characteristics.

Depression, anxiety, and stress symptoms were significantly higher among professors who participated in Phase 3 than among those who participated in Phases 1 and 2, while subjective distress was lower in Phase 2 of the study ( Table 2 ). Among students, the prevalence of depression and stress symptoms was higher in Phases 2 and 3, while anxiety was higher only in Phase 3. The prevalence of symptoms and distress was high in both occupational categories studied, but these were significantly higher among students (see Table 2 ; Figure 1A ). Professors were more likely to use adaptive coping strategies in the face of the pandemic, such as AC, PL, RE, PR, and AT whereas students were more likely than professors to use maladaptive strategies (SD, BD, SU, DN) ( Table 2 ; Figure 1B ). The use of problem-oriented strategies such as AC, PL, and IS increased from Phase 1 to Phase 3, for both students and professors. Among professors, the prevalence of acceptance was lower and substance use was higher in Phase 3.

Table 2 . Prevalence [ p 95% (CI)] of depression, anxiety, stress and subjective distress symptoms, and usual coping strategies mentioned in BriefCOPE by students and professors at the different phases of data collection.

Figure 1 . Distribution of students and professors according to the degree of being affected by symptoms of depression, anxiety, stress, and subjective distress (A) and according to the usual (mean ≥ 3) coping strategy (B) , considering respondents of the three phases of the study (total sample). Radar radius = % of participants using the coping strategy habitually (mean ≥ 3). AC: Active coping; PL: Planning; IS: Instrumental support; ES: Emotional support; RE: Religion; PR: Positive reinterpretation; SB: Self-Blame; AT: Acceptance; VE: Venting of emotions; DN: Denial; SD: Self-Distraction; BD: Behavioral disengagement; SU: Substance use; HU: Humor.

The likelihood of experiencing symptoms of depression, anxiety, and subjective distress was significantly higher among students, women, and those with a prior mental disorder diagnosis. Age was inversely associated with the likelihood of symptoms/distress in the three study phases ( Table 3 ). We clarify that age was included in the model, as it plays an important role in differentiating occupational categories and should therefore be considered.

Table 3 . Logistic regression model and odds ratio (OR) of symptom occurrence in relation to mental health according to sex, lifetime diagnosis of mental disorder (DiagTM), professional category (PC), and age.

The main concerns reported by students and professors regarding the pandemic suggest that the two occupational groups had distinct experiences. In the case of professors, the concerns originated from a single core, namely health concerns, from which branched out all other concerns from various spheres of life, particularly family ( Figure 2 ). Conversely, we observed 3 cores among students: health, which branched out and two main groupings (see Figures 2A , B ), family and COVID-19. From the health concern arose group A, which represents the uncertainty and spread of the pandemic (over time), while B is represented by more pragmatic concerns such as unemployment/employment, graduation/education, and money/finances. The family core (group C) is closely related to the health core and is mainly related to worries about the contagion/illness of a family member. The COVID-19 core (Group D) is closer to family than health and also reflects fear of contracting the virus and anticipation of vaccination.

Figure 2 . Similitude analysis of the main concerns of students and professors in the face of the pandemic. Student: 3 cores: health, which branched out and two main grouping (A,B) , family (C) and COVID-19 (D) . Professor: single core: health.

4 Discussion

This study shows that students and professors experienced symptoms of depression (≥33%), anxiety (≥34%), and subjective distress (≥40%), at different times during the pandemic and used various coping strategies. We also found that students (OR = 1.29–2.05; p  ≤ 0.001), women (OR = 1.39–2.13, p  < 0.001), and those previously diagnosed with a mental health disorder (OR = 2.76–3.25, p  < 0.001) were more likely to experience these symptoms. Additionally, our results indicated that professors are teaching young people who have been seriously impacted by the pandemic and require psychological support (e.g., conducting support or assistance actions, engaging in activities that help release tension, or practicing self-care). However, this is complicated by the fact that professors themselves were also experiencing symptoms and distress. Given these challenges, managers and educators need to focus their attention on the need to support mental health in the educational environment. Thus, the main objective of this study was to draw attention to this critical issue.

Tri Sakti et al. (2022) highlighted in a systematic review that the COVID-19 health crisis has had four main consequences on the school population: the major effects on mental health, the teaching-learning process, people’s quality of life, and physical health. The sudden disruption of the school ecosystem required rapid responses to the almost immediate and urgent application of distance education, which resulted in stress, anxiety, and uncertainty that accompanied the health crisis. This situation placed a significant cognitive burden on individuals across education systems and countries ( Keržič et al., 2021 ). This overload led to increasing emotional exhaustion, triggering more or less severe symptoms depending on individual repertoires, social support, and contextual factors ( Hadar et al., 2020 ; Pressley, 2021 ; Salmela-Aro et al., 2022 ).

Students are typically younger and tend to have less life experience and a smaller repertoire of coping strategies than older individuals. Due that, they rely more emotion-focused coping strategies or maladaptive strategies (see Figure 1B ), which can contribute to the maintenance or exacerbation of symptoms ( Restubog et al., 2020 ; Panayiotou et al., 2021 ). In addition, younger individuals were more likely to express their feelings as a coping strategy, which may have contributed to their more frequent reporting of affective symptoms. On the other hand, professors, being older, have a larger cognitive repertoire, which likely contributed to their more frequent use of adaptive coping strategies focused on problem solving, i.e., they used more planning and action skills to eliminate or overcome the daily effects of the pandemic. This leads to better cognitive restructuring of reality, better psychosocial adjustment, and consequently, lower prevalence of symptoms and distress ( Lazarus and Folkman, 1984 ). Better coping and satisfaction with online classes were observed to be strong determinants of academic achievement among students from 10 countries around the world, which serves as a protective factor for health and physical and psychological well-being ( Keržič et al., 2021 ).

The stage of life may be a factor that contributes to the experience of stress and mental health issues for students during the COVID-19 pandemic. The students who participated in the study were over 18 years of age, meaning that they either finished high school or were in various stages of higher education and thus in the process of defining a career and entering the labor market, whereas professors were already in a stable role. Career choice is a complex process and involves expectations and uncertainties. Harari (2018) warned that in the technological era, predictability in the labor market is no longer guaranteed, which increases the need for flexibility and adaptability to constant change. With the advent of the pandemic, the whole scenario of possibilities changed rapidly, and in the context of remote work, uncertainties about their choices and the future increased, which can be observed in our study ( Figure 2 ). While for professors, health was the core of their concerns, which is contextual and to be expected once they were in a stable professional role, for students the core of concerns was divided into the uncertainties about the future on the one hand ( Figure 2A Cluster) and the academic situation and employability on the other hand ( Figure 2B Cluster). This scenario may have contributed to the higher prevalence of symptoms and distress among students, which is supported by the data in the Organization for Economic Cooperation and Development report (2021) .

The sharp decline in spontaneous social interaction and the introduction of distance education are also important factors to be considered. According to Salmela-Aro et al. (2022) and Tonon (2021) , the academic/school environment facilitates contacts and social interactions, providing opportunities to build networks and friendships and space for identity and institutional bonds. With the closure of schools/universities, student engagement in extracurricular activities and peer relationships declined significantly. For young people, this meant a disruption of important socialization rituals, a reduction in personal contact, and increased feelings of loneliness, stress, and burnout ( Salmela-Aro et al., 2022 ). Population studies in the United States and New Zealand present data showing that the prevalence of loneliness among young people (18 to 25 years) has more than doubled since the onset of the pandemic ( Organisation for Economic Co-Operation and Development, 2021 ). It is worth noting that distance education professors also report feelings of loneliness. Telyani et al. (2021) highlighted the relationship between professors’ loneliness and their performance, engagement, job satisfaction, and well-being, and showed that keeping students motivated and engaged in distance education was an arduous task for professors. In general, students and professors differ in terms of their social support network (instrumental and emotional), with professors having a more contextualized cognitive repertoire and coping strategies. Khan and Kadoya (2021) also point to the significant relationship between loneliness and depression and caution the need for interventions that can minimize harm to mental health.

As mentioned earlier, despite the lower prevalence of symptoms in professors than in students, this does not mean that they are low; on the contrary, the prevalence found is alarming and deserves attention ( Table 2 ; 33.5–53.6%). Certainly, COVID-19 has profoundly changed the way education is practiced, requiring intense adaptation from those involved, often without institutional support or sufficient training. In addition, there are complicating factors, such as the enormous social and economic inequalities in the Brazilian population, which are even more evident in the face of distance education ( Santos, 2020 ; Sousa and Coimbra, 2020 ), making the process more difficult. Some studies also suggest that although technological resources have allowed continuity in the communication process, they often create a distance between students and professors that affects social interaction and increases psychological fatigue (technostress: high level of psychophysiological activation; a set of symptoms associated with an excess of information and psychological demands) ( Pinho et al., 2021 ), which can lead to physical and mental illness if not adequately managed. Our results show that the frequency of depression and stress symptoms ( Table 2 ) significantly increased 18 months after the introduction of distance learning compared to the initial phases of the pandemic, both among students (depression: 80.0–82.6%; stress: 67.5–72.1%) and professors (depression: 33.5–53.6%; stress: 44.9–45.8%). Additionally, there was a significant increase in the prevalence of anxiety among students during this period (59.5–65.3%).

Regarding the fact that women (professors or students: OR = 1.39–2.13, p  < 0.001) suffer more often from distress, we can support the following arguments: 1. women have more accentuated ruminative reactions than men, which can prolong anxiety and increase the impact of stressors on humor ( Almeida and Kessler, 1998 ; Campos et al., 2020 ); 2. women take on multiple responsibilities and tasks and society expects them to try harder and make fewer mistakes than men ( Foschi, 2000 ); and/or 3. men are encouraged to limit and hide their emotions ( Chaplin, 2015 ). Certainly, other arguments can be used to explain the differences found between men and women; however, we presented only these three because this study was not designed to identify which of these arguments were involved in these results. Thus, these arguments are only speculation, and the reader should consider them cautiously.

Campos et al. (2021b) highlighted the greater vulnerability of people diagnosed with a mental disorder (the observed values in the results of the present study were OR = 2.76–3.25, p  < 0.001), in which they reported that these people (1) may have greater emotional instability, (2) may have greater difficulty adapting quickly to changes in their routines, (3) may also have had a disruption in mental health care due to the pandemic, and (4) may have greater difficulty obtaining social support during isolation. Given the pronounced impact of this condition on symptoms and subjective distress, it is suggested that strategic care interventions be developed, such as support, counseling, intervention, and follow-up involving specialized professionals and promoting healthy lifestyles.

Given the data and arguments presented, we understand that educational systems need to strengthen their psychosocial support network and, in this direction, Hadar et al. (2020) recommend that professor education curricula, based on the COVID-19 experience, include the training and development of socio-emotional skills that they can use for themselves and students and others in the educational process for overall well-being. Among the possible techniques for developing these skills, the authors cite conducting case studies and teamwork on problems and challenges encountered in education during the pandemic, training in digital platforms and tools, presentation and familiarization with the topic of crisis management, and stress management techniques.

The first limitation of this study was the fact that it was part of a larger study, which made it impossible to obtain more detailed information about respondents’ job performance (e.g., for professors: number of hours/week worked, work experience, type of institution, and level of education in which they work; for students: course, period and level of the course, full-or part-time studies, screen time used in remote activities, among others), and therefore we recommend conducting future studies. Another limitation is the study design used (non-probability sample and online data collection), which may have limited access to the research for populations with lower levels of education and/or economic status, making it difficult to generalize the data.

A further limitation is that we conducted three independent and anonymous phases in the study, meaning that we cannot determine whether participants took part in just one phase or two or all three. We can also mention the significant decrease in the number of participants from the first to the subsequent phases. This may have occurred due to the increased online demands placed on people during the pandemic, which may have discouraged their participation after 6 and 12 months. However, given the pandemic scenario, this online strategy was feasible to collect information that would directly identify subjective distress in the population. Despite these limitations, we emphasize that there are still few studies in the literature that present data from students and professors at different times during the COVID-19 pandemic and that use large samples.

5 Conclusion

The prevalence of depression, anxiety, stress, and subjective distress symptoms was high among students and professors. Students, women, and those previously diagnosed with a mental disorder were more likely to have mental health symptoms or distress. During the pandemic, professors used more adaptive coping strategies than students. Health was the focus of professors’ concerns, while for students, future and labor market uncertainty were concerns derived from the health core. The results point to the need to strengthen psychosocial support for both professors and students.

Data availability statement

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

Ethics statement

The studies involving humans were approved by the National Research Ethics Committee of the Ministry of Health (CONEP) (CAAE 30604220.4.0000.0008). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

JC: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Supervision, Writing – original draft. LC: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing. MA: Conceptualization, Investigation, Methodology, Writing – review & editing. BM: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Writing – review & editing. BS: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Writing – review & editing. JM: Conceptualization, Investigation, Software, Supervision, Writing – review & editing.

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was supported by grants #2020/08239-6 and #2021/03775-0, São Paulo Research Foundation (FAPESP); and the National Council for Scientific and Technological Development – CNPQ (#303118/2021-0).

Conflict of interest

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

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

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Keywords: mental health, university, students, professors, pandemics

Citation: Campos JADB, Campos LA, Azevedo MAR, Martins BG, Silva BNS and Marôco J (2024) Mental health in times of pandemic from the perspective of professors and students. Front. Educ . 9:1353756. doi: 10.3389/feduc.2024.1353756

Received: 11 December 2023; Accepted: 26 March 2024; Published: 08 April 2024.

Reviewed by:

Copyright © 2024 Campos, Campos, Azevedo, Martins, Silva and Marôco. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Lucas Arrais Campos, [email protected]

• Open access
• Published: 10 April 2024

The burden of anxiety, depression, and stress, along with the prevalence of symptoms of PTSD, and perceptions of the drivers of psychological harms, as perceived by doctors and nurses working in ICUs in Nepal during the COVID-19 pandemic; a mixed method evaluation

• Shirish KC 1 ,
• Tiffany E. Gooden 2 ,
• Diptesh Aryal 1 ,
• Kanchan Koirala 1 ,
• Subekshya Luitel 1 ,
• Rashan Haniffa 3 , 4 ,
• Abi Beane 3 , 4 on behalf of

Collaboration for Research, Implementation, and Training in Critical Care in Asia and Africa (CCAA)

BMC Health Services Research volume  24 , Article number:  450 ( 2024 ) Cite this article

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The COVID-19 pandemic resulted in significant physical and psychological impacts for survivors, and for the healthcare professionals caring for patients. Nurses and doctors in critical care faced longer working hours, increased burden of patients, and limited resources, all in the context of personal social isolation and uncertainties regarding cross-infection. We evaluated the burden of anxiety, depression, stress, post-traumatic stress disorder (PTSD), and alcohol dependence among doctors and nurses working in intensive care units (ICUs) in Nepal and explored the individual and social drivers for these impacts.

We conducted a mixed-methods study in Nepal, using an online survey to assess psychological well-being and semi-structured interviews to explore perceptions as to the drivers of anxiety, stress, and depression. Participants were recruited from existing national critical care professional organisations in Nepal and using a snowball technique. The online survey comprised of validated assessment tools for anxiety, depression, stress, PTSD, and alcohol dependence; all tools were analysed using published guidelines. Interviews were analysed using rapid appraisal techniques, and themes regarding the drivers for psychological distress were explored.

134 respondents (113 nurses, 21 doctors) completed the online survey. Twenty-eight (21%) participants experienced moderate to severe symptoms of depression; 67 (50%) experienced moderate or severe symptoms of anxiety; 114 (85%) had scores indicative of moderate to high levels of stress; 46 out of 100 reported symptoms of PTSD. Compared to doctors, nurses experienced more severe symptoms of depression, anxiety, and PTSD, whereas doctors experienced higher levels of stress than nurses. Most (95%) participants had scores indicative of low risk of alcohol dependence. Twenty participants were followed up in interviews. Social stigmatism, physical and emotional safety, enforced role change and the absence of organisational support were perceived drivers for poor psychological well-being.

Nurses and doctors working in ICU during the COVID-19 pandemic sustained psychological impacts, manifesting as stress, anxiety, and for some, symptoms of PTSD. Nurses were more vulnerable. Individual characteristics and professional inequalities in healthcare may be potential modifiable factors for policy makers seeking to mitigate risks for healthcare providers.

Peer Review reports

Introduction

Between January 2020 and December 2021, the COVID-19 pandemic led to an estimated 18.2 million deaths [ 1 ]. Globally, healthcare systems were overwhelmed during the pandemic, with intensive care units (ICUs) receiving an unprecedented burden of patients [ 2 ]. In Nepal, the government first declared a lockdown on March 24, 2020, that lasted until July 21, 2020, and the second lockdown was announced on April 29, 2021, which was fully lifted on September 1, 2021 [ 3 ]. The first wave of the COVID-19 pandemic reached a peak of over 5000 cases a day in October 2020, and the second wave reached a peak of more than 9000 cases a day in May 2021, which was almost double [ 4 ]. Prior to the pandemic, Nepal reported a capacity of 1595 ICU beds across 194 hospitals and around 840 ventilators, equating to 2.8 ventilator-equipped ICU beds per 100,000 people [ 5 ]. To cope with the influx of COVID-19 patients, several existing postoperative wards and other high-dependency units of the hospitals were converted into improvised critical care units [ 6 ]. Globally, healthcare professionals (HCPs) and specifically those working in ICU and critical care services, arguably were at the frontline of the healthcare response. These HCPs faced the uncertainty of managing this new condition, extended working hours, limited personal protective equipment (PPE), and an increased risk of infection as they provide essential lifesaving interventions, including intubation and non-invasive respiratory management [ 7 , 8 ].

The impacts of the COVID-19 pandemic on the mental health and well-being of HCPs who worked during and after this global emergency are slowly becoming apparent. Research emerging from China, the USA, and Europe [ 9 ] describes a significant burden of psychological distress and symptoms synonymous with mental health conditions in HCPs. This is also evident from the limited studies that have been conducted in Nepal. For instance, one study conducted among 150 HCPs from outpatient clinics and inpatient wards caring for COVID-19 patients in Nepal reported that 38% of participants suffered from anxiety and/or depression [ 10 ]. Another Nepali study revealed that the prevalence of anxiety and depression among HCPs, including health assistants and support staff was 47% and 41%, respectively [ 11 ]. A larger online survey of 475 HCPs including pharmacists, paramedics and public health practitioners reported similar findings (42% had anxiety) and noted that nurses had a higher proportion of symptoms compared to other HCPs [ 12 ].. Whilst these studies, in conjunction with a meta-analysis, indicate that depression, anxiety, and post-traumatic disorder (PTSD) are highly prevalent among HCPs during the pandemic [ 9 , 10 , 11 , 12 , 13 ], fewer studies have explored the disparities between professionals’ roles, specifically among ICU workers, a group exposed to more advanced cases of COVID-19. Indeed a small study in Nepal comprising 96 nurses revealed that nurses who worked directly with COVID-19 patients experienced more severe symptoms of depression and anxiety [ 13 ]. The nature and characteristics of mental health symptoms appear to vary geographically, the HCPs’ role, their individual characteristics (age, gender) along with health system’s pre-existing resource capacity and ability to respond to increasing demand placed by events such as a pandemic. Understanding the mental health impact of ICU workers, any disparities between professional roles and drivers behind poor mental health in Nepal will help to identify what support is needed for ICU workers for pandemic preparedness; thus, providing important directions for investment in health systems strengthening.

We aimed to investigate the burden of anxiety, depression, stress, PTSD, and alcohol dependence among doctors and nurses in Nepal that worked in the ICU during the COVID-19 pandemic. We further sought to identify the factors driving the self-reported burden of psychological distress by exploring the lived experiences of these two different professional groups, and how these experiences impacted their psychological health and well-being.

Study design

We undertook a mixed-methods cross-sectional study [ 14 ] in Nepal with ICU doctors and nurses, combining an online questionnaire consisting of validated self-assessment tools combined with semi-structured interviews. The following self-reporting psychological assessment tools were used, given they have been used in previous studies in other settings and their widely validated in a variety of settings: Beck Anxiety Inventory (BAI) [ 15 ], Beck Depression Inventory (BDI) [ 16 ], Perceived Stress Scale (PSS) [ 17 ], PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-5 (PCL-5) [ 18 ] and Alcohol Use Disorder identification Tool (AUDIT) [ 19 ]. BDI, BAI, and AUDIT have been validated in Nepal [ 20 , 21 , 22 ] and the PSS has been tested for reliability and correlation in Nepal [ 23 ]. Whilst the PCL-5 has not been validated in a Nepali setting, it was piloted (along with all other assessment tools used) with 20 people before the study commenced. Participants were given the flexibility to complete the questionnaire in either Nepali or English language. Despite this option, all participants opted to respond in English.

Ethics approval

was granted from the Nepal Health Research Council (approval number: 176/2021 P). All participants provided informed consent electronically before completing the online questionnaire. Participants from the qualitative component provided further informed verbal consent before the interview commenced.

In 2020, Nepal reported a capacity of 1595 ICU beds across 194 hospitals and around 840 ventilators, equating to 2.8 ventilator-equipped ICU beds per 100,000 people [ 5 ]. A year later, Nepal was under a state of health emergency, with patients being turned down due to a lack of ICU beds, oxygen, and ventilators [ 24 ].

Participants and recruitment

Doctors and nurses with experience in caring for COVID-19 patients in Nepalese ICUs were eligible for participation. Initially doctors registered with the Nepalese Society of Critical Care Medicine (NSCCM) [ 25 ] and nurses registered with the Critical Care Nurses Association of Nepal (CCNAN) [ 26 ] were contacted and invited to participate. Both organisations consist of voluntary memberships and represent the doctors and nurses working in a critical care setting in Nepal. At the time of recruitment, there were 187 doctors and 104 nurses registered at these organisations. This initial purposive sampling was augmented by snowballing techniques, whereby respondents were invited to forward the questionnaire link to other doctors or nurses working in ICUs [ 27 ]. Following completion of the questionnaire, respondents were invited to participate in a virtual interview. A convenience sample of 20 participants (a number which, based on the literature, was likely to provide saturation of findings [ 28 ]) was subsequently scheduled for an interview.

Study materials and data collection

The questionnaire was developed using an online survey platform (Google Forms) [ 29 ]. The questionnaire was piloted for readability and responder reliability with twenty HCPs based in Nepal, prior to roll out, who did not participate in the final analysis. Questionnaire content included socio-demographic information; age, sex, professional role and experience, degree of schooling, and home living arrangements; factors which had been identified as being important in the burden of psychological distress and impact on family life in similar research conducted during the previous SARS pandemic as well as the current COVID-19 event [ 30 ]. Participants could opt out of the study at any time. Participants could only complete the questionnaire once, and all survey responses were anonymous. Participants were signposted to healthcare services available to them should they be suffering from any distressing, mild, moderate or severe mental health symptoms. Invitations to participate in the questionnaire were sent out from 20th May 2021, and the questionnaire was closed to responses on 2nd October 2021.

The semi-structured interview topic guide was co-developed between doctors and nurses working in ICUs in Kathmandu. Co-design was used to ensure the sensitivity and appropriateness of the questions. None of the doctors and nurses involved in the codesign of the topic guide participated in the study proper. The qualitative component was aimed to augment the quantitative findings by providing an understanding of what social, organisational, and environmental factors were related to HCPs’ mental health. Topic guide questions focused on HCPs’ perceptions of their experiences of working during the pandemic and explored social, organisational, and environmental factors that may have influenced their self-reported burden and symptoms of psychological distress. These factors were selected from a review of the findings of the previously published meta-analysis and other studies conducted in Nepal [ 9 , 10 , 11 , 12 , 13 ]. The interview questions were piloted with five HCPs for interpretability and interviewer consistency. All interviews were conducted via video conferencing (Zoom) [ 31 ] between September 2021 and March 2022. Five ICU nurses with experience in conducting interviews and mixed methods research led the data collection following training on the topic guide. To ensure there was no prior relationship between the interviewer and the participant, interviewers were assigned to participants that worked in different ICUs than themselves and were not known to the interviewee. No one other than the interviewer and the participant was present for each interview, and interviews were conducted at the time chosen by the interviewee. Rapid assessment procedure (RAP) sheets were used for note-taking during the interviews [ 32 ]. Commonly used in rapid evaluations - designed to improve the rapidity and replicability of research during public health emergencies - RAP sheets help reduce the need for long-form transcription and encourage reflexivity for both interviewers and researchers, reduce interviewer bias, and enable validation of internal consistency with coding [ 33 ]. The RAP sheet contained the summary of questions from the topic guide, and the interviewers took notes of what the participants said regarding each question during the interview.

Data analysis

Descriptive statistics were used to describe participants’ demographics and professional profiles. Psychological health and well-being assessment tools from the questionnaire were analysed using published guidelines. For the BDI, each of the 21 items corresponding to a symptom of depression was summed for each participant to give a single total score [ 16 ]. With each item ranging from 0 to 3 points, a total score of 13 or less was considered minimal to no depression, 14 to 19 as mild depression, 20 to 28 as moderate depression, and 29 to 63 as severe depression [ 16 ]. Data is also presented separately for suicidality (question 9 from the BDI) whereby anyone that said they have thoughts about or plans to kill themselves is said to have experienced suicidality. The BAI scores reported included the 21 symptoms of anxiety that ranged between 0 and 63 points [ 15 ]. The values for each symptom were summed, and a total score of 0 to 7 was interpreted as a minimal level of anxiety, 8 to 15 as mild, 16 to 25 as moderate, and 26 to 63 as severe anxiety [ 15 ]. Scores on the PSS ranged from 0 to 40, with higher scores indicating higher perceptions of stress [ 17 ]: scores ranging from 0 to 13 were considered low descriptors of stress; 14 to 26 moderate; and 27 to 40 were considered higher levels of perceived stress. For alcohol use disorder reported using AUDIT [ 19 ], a score of 0 indicated no previous or current alcohol use; a score of 1 to 7 suggested low-risk consumption; 8 to 14 hazardous or harmful alcohol consumption; 15 or higher indicated the likelihood of alcohol dependence (moderate to severe alcohol use disorder). The PCL-5 included 20 items with a score range of 0 to 80 and a score of 33 or higher, indicating the presence of PTSD [ 18 ]. A sensitivity analysis was conducted for the BDI, BAI and AUDIT scores based on local validation studies whereby a score of 15 or lower from the BDI indicated no depression [ 20 ], 12 or lower from the BAI indicated no anxiety [ 21 ], and a score of 11 or above from the AUDIT indicated discriminate dependent drinkers [ 22 ].

RAP sheets, along with interviewer notes, were reviewed by the research team before analysis to ensure information was complete. SK, KK and AB used a constant comparative method, coding data following each round of interviews and then reflecting back on the summary of the codes together with the interviewers to promote the accuracy of findings and reduce recall and interviewer bias. In addition, emerging themes identified following each round of coding were used to guide subsequent interviews [ 34 ]. The broader research team met following each coding round to review the findings and reflexivity [ 35 ]. Categories and the subsequent themes (‘drivers’) were developed through the iterative process of interviewing, coding, analysing, and reviewing.

We invited 120 doctors and 341 nurses to participate. A total of 21 doctors and 113 nurses responded, all of which completed the BDI, BAI, PSS, and AUDIT questions; 100 completed the PCL-5 (16 doctors and 84 nurses). Nearly all nurses were female (99%, n  = 112), whereas most doctors were male (81%, n  = 17). The characteristics of respondents are described in Table  1 .

50% ( n  = 67) of respondents reported experiencing symptoms associated with moderate to severe anxiety, and a further 27% ( n  = 36) scored for mild anxiety as a result of working in the ICU during the COVID-19 pandemic (Table  2 ). Anxiety levels (and associated symptoms) were more pronounced in nurses than doctors, with 55% ( n  = 62) of the former scoring moderate to severe on the anxiety scale, compared to 24% ( n  = 6) of the latter. 21% ( n  = 28) of respondents described symptoms associated with moderate to severe depression, with a near-even split between nurses and doctors. Three-quarters of respondents ( n  = 114; 85%) had scores indicative of moderate to high levels of stress; this proportion was higher among doctors ( n  = 19; 91%) compared to nurses ( n  = 95; 84%). Of the 100 individuals that completed the PCL-5 assessment (16 doctors and 84 nurses), 45% ( n  = 46) reported a constellation of symptoms closely associated with PTSD, with a higher prevalence among nurses ( n  = 40; 47%) compared to doctors ( n  = 6; 38%).

Using cut-off scores from Nepali validation studies, 45 (34%) participants were experiencing mild, moderate or severe depressive symptoms, 80 (60%) were experiencing mild, moderate or severe anxiety symptoms, and 3 (2%) were considered discriminate dependent drinkers. These results are in line with our main analysis, including that a greater proportion of nurses were still found to suffer from depression and anxiety symptoms (supplementary Table 1 ).

Forty-six respondents to the online questionnaire volunteered to participate in the subsequent semi-structured interviews. Twenty participants were approached and consented to an interview: 16 were nurses (all female), and 4 were doctors (1 female, 3 male). On average, each interview resulted in 45 to 60 min of qualitative data. Saturation was met within the first 15 interviews, and findings were consistent between the coders and the research team. Analysis and synthesis of the interviews revealed nine themes, which, when codified, can be described as three key drivers of the psychological symptoms and impacts on mental well-being experienced by the interviewees: social stigmatism, physical and emotional safety, and organisational support. (Fig.  1 ). During the interviews, HCPs further described some of the coping strategies that they found helpful in mitigating the impacts experienced and may provide insights for future pandemic preparedness. These three themes, the drivers, and coping strategies, are explored below, along with quotes from the respondents.

Coding tree for the four main drivers for psychological distress

Social stigmatism

Interviewees described experiencing feelings of social stigmatisation as a result of interactions with their families, peers, as well as from the wider public. Examples of stigmatism experienced included physical avoidance from neighbours and community members when the HCP travelled to and from and around their home, especially when dwellings were in shared buildings and common areas.

“My house owner avoided talking and meeting me because I worked with COVID patients.” [N]. “I have an elderly family member, and I was afraid and worried [for them] when I came back from duty.” [N].

Interviewees described how rumours would spread within the community, notably related to concerns of risk of co-infection or cross-infection, either directly from parent to child or indirectly via friends and extended family. Some HCPs were asked or elected to stay away from their home so as to reduce the stigma to them and their family and in an attempt to reduce the risk of co-infection, particularly when they had vulnerable family members. Interviewees described how this self-selected or enforced separation and isolation resulted in feelings of rejection, physically and emotionally heightened feelings of stress and anxiety, alongside the threat to physical and emotional safety.

Physical and emotional safety

Increased workload and an enforced change in working pattern/ shift structures were experienced by all the HCPs interviewed. These longer overall working hours, increased duration of shift patterns, and enforced working rotas were perceived as resulting in a loss of physical and emotional safety by the interviewees. Feelings of loss of control, insomnia, or disruption to sleep patterns, alongside physical discomfort through sustained working in personal protective equipment, often in hot and humid temperatures. This physical and mental endurance contributed to feelings of emotional stress and anxiety.

“Shift frequency was increased, and I only got one night off in a week. Sometimes I had to work extra hours, which was very stressful.” [N]. “My sleep pattern had changed, I felt restless and was afraid about COVID” [D].

The change in shift structure and in working patterns meant for some HCPs enforced separation from family and friends whereby HCPs sought accommodation away from family or in temporary lodgings. This again resulted in isolation and additional strain on other family members so as to provide care for HCP’s dependents.

“I had to involve other family members to arrange for the medication and care of my grandmother” [N].

Increased working hours and changes in working patterns further had physical impacts; participants described skipping meals or having limited time to eat. The need to wear personal protective equipment (PPE), and indeed the risks to safety when PPE was not available, associated risks of non-availability of equipment, brought with it a risk to physical and emotional safety. HCPs interviewed reported skin lacerations, irritation, and discomfort whilst wearing equipment in hot, humid working environments.

“We had to frequently change the PPE and masks, which has caused skin problems that still exist.” [N].

Organisational support

Interviewees found the COVID-19 pandemic brought new and often enforced work responsibilities, some of which were associated with high levels of professional anxiety, stress, and uncertainty. A professionally challenging situation, even for those with many years of ICU working experience. HCPs faced emotionally challenging tasks such as dealing with end-of-life situations (particularly without relatives of the patient present) and having to comfort relatives over the phone, of which they received limited to no training or support on handling such situations.

“I went through an emotional breakdown while dealing with the end of the life situation of patients without the presence of family members in the COVID ICU… I felt sad when a young patient lost their lives” [D]. “Accommodation or isolation facilities should be provided by the hospital” [D]. “If incentives were provided in time and staff were provided with health insurance it would motivate us” [N].

Ever-changing role and responsibilities created anxiety for HCPs as to what care to deliver, and the rapidity and uncertainty of care were associated with feelings of vulnerability. Interviewees expressed how they wished there was a need for greater organisational support to better cope with the frequent updates and changes to practice. Furthermore, HCPs expressed concerns regarding a shortage of staff and the lack of mental health counselling and support, accommodation on-site at the hospital, and transportation to and from work.

“Mental health support or counselling facilities were not provided. It should be there… seniors and hospital staff should also talk to the staff to know the situation.” [N]. “Safety of healthcare workers should be the priority and nurse-patient ratio should be maintained to provide quality care to the patients… hospital should have recruited more staff.” [N].

Coping strategies

Participants described various ways in which they coped with the emotional, physical, social, and professional impacts of working through the pandemic. This included speaking with family and friends about the pressures they were under, taking up activities in their off time, such as gardening and reading, and using media entertainment such as music, movies, and shows. A few participants also mentioned that comparing the situation in Nepal to other countries (i.e., keeping up-to-date with the news) also helped them cope. Others mentioned that detachment from social media and more self-awareness through meditation helped.

“I ventilated my feelings with friends and family. Listening to soothing music also helped me cope with the stress.” [N]. “I coped by gardening with my sister in my home.” [N]. “I… watched the news that compared the death rates, which was low compared to others.” [D].

The COVID-19 pandemic’s impact on healthcare services and population health internationally is unprecedented in recent times. As healthcare professionals, policymakers, and researchers work to strengthen services in preparation for future pandemics now and mitigate the long-term impacts on individual and population health, understanding the impact on and perspectives of doctors and nurses at the frontline of care can provide important learning regarding the individuals characteristics and professional, social and economic drivers which may increase the risk of psychological impacts.

Mandated and enforced changes in role, specifically in working hours and shift patterns, were a key driver of psychological anxiety and distress. Within hospitals in Nepal, many departments were closed, and stay-at-home orders meant that outpatient or clinical services all but ceased. This resulted in an increased role and scope for critical care trained staff, and in contrast to other health systems (such as the UK) where healthcare staff were redeployed to ICU, there was a separation for ICU staff even from their professional peers working in other specialties. The increased scope and uncertainty of the HCP’s role, along with limited choice in redeployment in the ICU was another driver of poor mental health- and dominated nursing participants’ experiences. Interviewees described how these changes impacted not only themselves but the multigenerational families for whom many cared for. This enforcement of role change, and the related descriptions of the drivers for these impacts as experienced by participants in this study point not only to the differences in roles between nurses and doctors; but also highlights disparities in autonomy, advocacy for role change during international emergencies, and the implications of work on home and family life [ 36 ].

Giving staff choice to select shift patterns and ensuring the opportunity to have periods of rest to reconnect with family and have self-care is needed. Consultation and shared decision-making, even in times of restricted choice, are associated with improved perceptions of work from staff and may result in reducing psychological distress and promoting emotional safety, which is, in turn, associated with better outcomes for patients [ 37 , 38 ]. However, nurses in Nepal, as with many health systems, may have less opportunity for strategic and organisational decision making in response to public health emergencies. The impact of ongoing disparities between professionals and their agency to advocate for wellbeing and safety warrants further research.

Nurses were disproportionately burdened by both occurrence and severity of symptoms of anxiety and depression as a result of their work during the pandemic when compared to doctors.

Nearly half of all respondents had symptoms of anxiety and PTSD (again more prevalent in nurses), and the burden of anxiety symptoms was higher than the reported 22–33% from a recent umbrella review [ 39 ]. The burden of stress we report was also higher than a smaller study conducted in Nepal during the pandemic, which reported stress among 53.2% of healthcare professionals working in hospitals, primary health centres, pharmacies, and health posts in Nepal [ 40 ]; it was also higher than a meta-analysis of published studies exploring the incidence of both stress (57%) and PTSD (22%) among all cadres of healthcare workers [ 41 ]. One reason for the higher reported symptoms in our study may be the focus on ICU workers and their role in the management of end-of-life care. Indeed, our results for depression and anxiety are comparable to a study involving nurses working directly with COVID-19 in Nepal [ 13 ]. Studies conducted elsewhere in Asia have highlighted this positive relationship between ICU experiences and poor mental health [ 42 ].

Nurses in Nepal, as with many other countries, are more likely to be female, younger in age, and have less opportunity for graduate study; and have lower earning potential than physician colleagues [ 43 ]; all characteristics associated with increased risk of poorer mental health outcomes [ 44 ]. Exploration into the disparities of the psychological and health impacts of COVID-19 on different cadres of healthcare workers is emerging. A systematic review conducted in 2020, identified 27 studies which sought to explore the disparity in impacts of the pandemic on HCP’s psychological well-being. The findings from the review are in line with ours, indicating that the burden of symptoms for anxiety, depression, and PTSD is higher in nurses compared to doctors [ 45 ]. Notably only a few of these studies used validated tools for assessment of specific symptoms of anxiety, depression, or substance misuse [ 45 ]. Our study serves to strengthen the evidence of the vulnerability of nurses.

Nepal, like many other lower and middle-income countries in South and Southeast Asia, enforced large-scale lockdowns and restrictions of movement for all but essential healthcare and municipal staff [ 46 ]. As such, social stigmatism, physical and emotional safety, and organisational support were key drivers behind the elevated symptoms of psychological distress in ICU HCPs and may be a key determinant of differences between health systems internationally. Furthermore, the family responsibilities and social circumstances for nurses, contributed to their experiences of isolation, rejection, vulnerability, physical discomfort, and strain. These drivers mirrored those reported from Europe; and may reflect differences experienced by nurses as a result of their gender, and role norms of primary family carers within society [ 44 ].

Interviewees from both professional groups expressed concern at the absence of preparedness and support they felt from their employing institutions. This is notable given the ongoing investment in pandemic preparedness and the potential to make changes now to prepare for the next pandemic or public health emergency. Interventions such as resilience training, scenario-based simulation training, and group exercises based on psychoeducation and cognitive behavioural therapy (CBT) principles have proved effective in reducing anxiety, depression, stress, and PTSD among doctors and nurses while simultaneously improving their ability to work in unprecedented situations in other sectors [ 47 ]. Similar provisions may be valuable for ICU-based healthcare professionals and are deliverable online, making rollout potentially more feasible.

Strengths and limitations

A strength of this study is the exploration of participants’ perspectives on the drivers behind the burden of poor mental health described in ICU HCPs. This mixed methods approach offers insights into doctors’ and nurses’ unique individual, social and professional characteristics that may be associated with increased risk of distress. These differences and their potential for disparity in impacts on health and wellbeing should be of interest to policymakers and healthcare facility managers involved in future pandemic preparedness. However, the study has some limitations to acknowledge. Given the use of the snowball technique, we were able to ensure a high number of respondents, but as a consequence, we were unable to track the number of respondents that came from using this technique compared to those initially invited from the NSCCM and CCNAN. Therefore, a response rate and, subsequently, a non-response rate could not be reported. We did not collect information on the level of training in critical care that participants received; trained health professionals are likely to have additional skills in how to handle the potential stressful environment in critical care settings. Also, due to the lack of validation of the PCL-5 in Nepal, the results of this assessment tool should be interpreted with caution. The survey tools used for this study have not been validated in an online format. However, given these tools were self-reporting, and were piloted and administered in English, the online format is thought to have minimal impact on the results. Additionally, participants for the qualitative component were recruited based on convenience sampling; therefore, the diversity of the sample may not be optimised. We acknowledge that recall bias may be present in the participants during the interview, given they were recalling their experiences throughout the pandemic for up to 24 months prior to the interview; however, we hope the piloting of the interviews, the use of multiple researchers to code the data, and the constant comparative nature of the evaluation will mitigate this potential.

The COVID-19 pandemic negatively impacted the mental health of HCPs worldwide. This study strengthens existing evidence that nurses were (and may remain) at increased risk of both cross infection and may also be more vulnerable to psychological impacts including anxiety, depression and PTSD than their professional colleagues. In addition, critical care staff may be at even greater risk, due to the uniqueness of their role which includes prolonged periods of time with infected patients, frontline role in managing end of life care, and as described here, limited ability to advocate for changing role and working patterns during an emergency. Professional hierarchies, and social-economic and gender profiles unique to nurses, may be potential drivers for these disparities, and warrants further research. Learning from the ICU HCPs’ experiences during the COVID-19 pandemic may inform future preparedness strategies e to mitigate short and long-term mental illness among ICU HCPs in future pandemics.

Data availability

The interview guide is available in the Figshare repository,

https://doi.org/10.6084/m9.figshare.24247384.v1 .

The data supporting the conclusions of this article are available in the Figshare repository, https://doi.org/10.6084/m9.figshare.23999790.v1 .

Abbreviations

Coronavirus disease 2019

Intensive care unit

Healthcare professional

Personal protective equipment

Post-traumatic stress disorder

Nepalese Society of Critical Care Medicine

Critical Care Nurses Association of Nepal

Beck Anxiety Inventory

Beck Depression Inventory

Perceived Stress Scale

PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-5

Alcohol Use Disorder Identification Tool

Rapid assessment procedure

Cognitive behavioural therapy

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Acknowledgements

We thank the volunteers who took the time to interview the participants: Radhika Maharjan, Dipika Khadka, Anita Bashyal, Samina Amatya, and Roshani Kafle. We also want to thank Dr. Rohini Nepal and Jugmaya Chaudhary of Rhythm Neuropsychiatry Hospital and Research Centre for their contribution to advising and reviewing the self-reporting psychological assessment tools used in the questionnaire. We would also like to thank Transcultural Psychosocial Organisation (TPO) Nepal and Dr. Nabaraj Koirala for the permission to use the Nepali-validated version of BDI I and BAI for the study. We additionally thank Nilu Dullewe, who helped in coding the qualitative data. For the ongoing mutual support for improvements in ICU care, we would also like to acknowledge and thank members of the CCAA.

CCAA members

Diptesh Aryal, Shirish KC, Kanchan Koirala, Subekshya Luitel, Rohini Nepal, Sushil Khanal, Hem R Paneru, Subha K Shreshta, Sanjay Lakhey, Samina Amatya, Kaveri Thapa, Radhika Maharjan, Roshani Kafle, Anita Bashyal, Reema Shrestha, Dipika Khadka and Nilu Dullewe.

This study was funded by a Wellcome Innovations Flagship Programme grant (Wellcome grant number: 215522/Z/19/Z). They had no role in the design, analysis, or reporting of this protocol.

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Shirish KC, Diptesh Aryal, Kanchan Koirala & Subekshya Luitel

Institute of Applied Health Research, University of Birmingham, Birmingham, UK

Tiffany E. Gooden

Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK

Rashan Haniffa & Abi Beane

Mahidol Oxford Tropical Medicine Research Unit, Bangkok, Thailand

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• Diptesh Aryal
• , Shirish KC
• , Kanchan Koirala
• , Subekshya Luitel
• , Rohini Nepal
• , Sushil Khanal
• , Hem R Paneru
• , Subha K Shreshta
• , Sanjay Lakhey
• , Samina Amatya
• , Kaveri Thapa
• , Radhika Maharjan
• , Roshani Kafle
• , Anita Bashyal
• , Reema Shrestha
• , Dipika Khadka
•  & Nilu Dullewe

Contributions

All authors conceptualised this study. SK, DA, AB, RH, and SL developed the protocol, study methods, and materials. KK and SL facilitated the data collection, supervised by SK and DA. Data were analysed by SK, AB, KK, and TEG. SK and TEG wrote the drafts of the manuscript, and all authors reviewed the manuscript and consented to it being submitted. AB is the senior author.

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Correspondence to Diptesh Aryal .

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Ethics approval and consent to participate.

Ethics approval was granted from the Nepal Health Research Council (approval number: 176/2021 P). All participants provided informed consent electronically before completing the online questionnaire. Participants from the qualitative component provided further informed verbal consent before the interview commenced.

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KC, S., Gooden, T.E., Aryal, D. et al. The burden of anxiety, depression, and stress, along with the prevalence of symptoms of PTSD, and perceptions of the drivers of psychological harms, as perceived by doctors and nurses working in ICUs in Nepal during the COVID-19 pandemic; a mixed method evaluation. BMC Health Serv Res 24 , 450 (2024). https://doi.org/10.1186/s12913-024-10724-7

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Published : 10 April 2024

DOI : https://doi.org/10.1186/s12913-024-10724-7

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Study finds boys' mental health more impacted by COVID-19 pandemic than girls'

T he COVID-19 pandemic had a greater impact on boys' mental health than girls, contrary to the findings of other studies, according to new research led by scientists at University of Liverpool, Manchester Metropolitan University, University of Reading, and King's College London.

These findings could have a significant impact on referral of adolescents to mental health services and on diagnoses, and greater awareness of age-related changes in mental health symptoms is needed by clinicians, educators and parents, say researchers.

Researchers used their unique dataset with repeated measurement pre and during the pandemic, and, crucially, took into account the developmental differences in symptoms between boys and girls aged 11–14 years.

According to the study, initial reports of a pandemic-related increase in depression in young adolescent girls could be explained by a natural rise in these symptoms as they get older. In contrast, pandemic-related increases in boys' depression and both boys' and girls' behavioral problems may have been masked by maturational changes over early adolescence.

The paper , "COVID-19 pandemic impact on adolescent mental health: a reassessment accounting for development," was published in the European Journal of Child and Adolescent Psychiatry .

The team were able to draw the conclusions using the unique longitudinal dataset: Wirral Child Health and Development Study (WCHADS). The study was also unique in capturing reports on depression in young adolescents' health from the parents and self-reports from the children themselves at this key stage. This indicated an over-reporting of a pandemic effect on girls' symptoms of depression by parents, while under-reporting the pandemic effect on boys.

Professor Helen Sharp, Professor of Perinatal and Child and Adolescent Clinical Psychology, University of Liverpool said, "We have identified significant changes in the pattern of mental health needs of young people due to the pandemic.

"Our study revealed adverse effects of the pandemic, with increases in behavioral problems in both boys and girls and increased depression symptoms in adolescent boys in particular. Emotional difficulties may not be recognized easily by parents or schools. However, raised awareness should help ensure more young people are directed to sources of support and treatment."

Lead author Nicky Wright, a Lecturer in Psychology at Manchester Met, said, "Because of the general decrease in boys' depression with age, and the general messaging about the impact of the pandemic being greater on girls, it is likely that boys' mental health needs are being missed, but also there may be more referrals for boys than will be anticipated."

"Overall, it is very important to take aging into account when considering diagnosis and prognosis in early adolescence, because these maturational shifts may mask or over-state actual change in symptoms. The differences between the parents' reporting and the adolescents self-report also potentially have important implications because it is typically parents who initiate referrals to child and adolescent mental health services for young people."

The WCHADS is led by Jonathan Hill, Professor of Child and Adolescent Psychiatry at University of Reading and Helen Sharp, Professor of Child and Adolescent Clinical Psychology at the University of Liverpool. Statistical analysis is led by Andrew Pickles, Professor of Biostatics at King's College London.

More information: N. Wright et al, COVID-19 pandemic impact on adolescent mental health: a reassessment accounting for development, European Child & Adolescent Psychiatry (2024). DOI: 10.1007/s00787-023-02337-y

Provided by University of Liverpool

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Regions & Countries

Key facts about title 42, the pandemic policy that has reshaped immigration enforcement at u.s.-mexico border.

The Biden administration is seeking to end the use of Title 42 , a pandemic-era policy that has led the Border Patrol to turn away hundreds of thousands of migrants attempting to enter the United States at the U.S.-Mexico border over the past two years. The administration’s move to end the Title 42 policy has been cheered in some corners and criticized in others , and opponents of the decision are challenging it in court and in Congress .

As the debate over the use of Title 42 unfolds, here are answers to key questions about the policy, based primarily on information from the Centers for Disease Control and Prevention (CDC) and Customs and Border Protection (CBP), the agency that oversees the Border Patrol.

This Pew Research Center analysis examines the immigration policy known as Title 42, which the Biden administration is seeking to end by May 23, 2022. The analysis is based primarily on information from the Centers for Disease Control and Prevention (CDC) and Customs and Border Protection (CBP), the agency that oversees the Border Patrol.

The Border Patrol provides statistics on migrant “encounters” at the U.S.-Mexico border. Encounters refer to two distinct kinds of events: expulsions under Title 42, in which migrants are immediately expelled to their home country or last country of transit, and apprehensions under Title 8, in which migrants are detained in the United States, at least temporarily.

It is important to note that encounters refer to events, not people, and that some migrants are encountered more than once. In fact, repeat border crossers have accounted for around a quarter of total encounters at U.S. borders in recent years. As a result, the number of encounters overstates the number of distinct individuals involved.

This analysis only includes encounters reported by the U.S. Border Patrol at the U.S.-Mexico border. It excludes encounters reported by the Office of Field Operations and those at the U.S.-Canada border.

What is Title 42?

Title 42 refers to a rarely used section of the U.S. Code that dates to 1944. The law empowers federal health authorities to prohibit migrants from entering the country if it is determined that doing so could prevent the spread of contagious diseases.

The CDC invoked Title 42 at the beginning of the U.S. coronavirus outbreak in March 2020, giving Border Patrol agents the authority to swiftly expel migrants trying to enter the U.S. instead of allowing them to seek asylum within the country, as had long been the policy before the pandemic. Migrants expelled from the U.S. under Title 42 are returned to their home country or most recent transit country.

Part of the rationale for invoking Title 42 was to avoid holding migrants in crowded U.S. immigration facilities as the highly transmissible coronavirus was spreading. But some advocates, elected officials and others have criticized the policy as more of an effort to restrict immigration to the U.S. than a public health strategy.

Why is the Biden administration seeking to end the use of Title 42?

In announcing its decision to end the policy after more than two years, the CDC cited “current public health conditions and an increased availability of tools to fight COVID-19,” including vaccines that can be distributed to migrants who are arriving at the border.

The Biden administration had initially planned for the policy to end on May 23, but a federal judge and members of Congress are considering putting that plan on hold amid concerns that the decision could lead to a surge in migration in the weeks and months ahead.

The CDC already ended the use of Title 42 for one group of migrants – unaccompanied minors – in March. It is currently seeking to end the policy for two other groups of migrants: single adults and people traveling in families.

What is the alternative to Title 42?

Before the CDC invoked Title 42, the Border Patrol handled migrants under a separate section of the U.S. Code known as Title 8, which deals with border enforcement.

Under Title 8, migrants typically can seek asylum in the U.S., citing a credible fear of persecution or other threats in their home country. The Biden administration has said that it would return to Title 8 enforcement practices after the Title 42 policy ends. ( This infographic from the Congressional Research Service shows how immigration enforcement practices work under both Title 8 and Title 42. The Border Patrol has relied on both approaches during the pandemic.)

A return to pre-pandemic enforcement practices does not necessarily mean that migrants would be allowed to enter and remain in the country. Many of them would need to wait in Mexico until their asylum claims can be decided – the result of a Trump administration policy that the Biden administration has kept in place under court order .

Migrants who cannot establish a legal claim to remain in the country would face removal from the U.S. and potentially other penalties. For example, those who are repeatedly caught attempting to enter the U.S. without authorization could be prosecuted criminally, as they frequently have been in the past .

How has immigration enforcement at the U.S.-Mexico border changed in the era of Title 42?

The Border Patrol tracks migration patterns at the southwestern border through a metric known as “encounters.” The term refers to two distinct kinds of events: expulsions, in which migrants are immediately removed from the U.S. under Title 42, and apprehensions, in which migrants are detained in the U.S., at least temporarily, under Title 8.

The Border Patrol has retained some discretion over whether to process migrants under Title 42 or Title 8, but most encounters during COVID-19 have ended in expulsion under Title 42.

Overall, there were nearly 2.9 million encounters with migrants along the U.S.-Mexico border between April 2020, the first full month after Title 42 went into effect, and March 2022, the most recent month with available data. Nearly 1.8 million of those encounters, or 61%, resulted in migrants being expelled under Title 42. The roughly 1.1 million remaining encounters ended in migrants being apprehended under Title 8.

It’s important to note that while the number of migrant encounters has risen sharply during the pandemic , the number of individuals encountered is considerably lower. That’s because around a quarter of migrant encounters at U.S. borders during the pandemic have involved repeat crossers . By contrast, in the fiscal year immediately preceding the pandemic, only 7% of migrant encounters involved repeat crossers. Title 42 may have contributed to the increase in repeat border crossers during COVID-19 since those who are expelled from the U.S. under the policy can try to enter the U.S. again without being subject to certain penalties they might otherwise face under Title 8.

Who has been expelled from the country under Title 42?

Almost nine-in-ten of the nearly 1.8 million expulsions that have taken place under Title 42 since April 2020 have involved single adults, while the remainder have involved people traveling in families (11%) or unaccompanied minors (1%).

Mexico is by far the most common origin nation of those who have been expelled under Title 42. Six-in-ten of those who have been expelled under Title 42 have been from Mexico, while 15% have been from Guatemala, 14% have been from Honduras, 5% have been from El Salvador and 6% have been from other countries.

How did the use of Title 42 change from the Trump administration to the Biden administration?

Both administrations leaned heavily on Title 42 in their immigration enforcement practices at the U.S.-Mexico border during the pandemic. But the Trump administration did so more than the Biden administration, at least when looking at the percentage of all encounters that ended in expulsion from the country under Title 42.

Under the Trump administration, 80% or more of monthly migrant encounters at the U.S.-Mexico border resulted in expulsion from the U.S. under Title 42. That percentage declined under Biden, who had pledged during his campaign for the White House to reverse some of Trump’s immigration policies . Even during the Biden administration, however, Title 42 expulsions have remained common: In March 2022, 51% of all migrant encounters at the southwestern border ended in expulsion under Title 42.

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Migrant encounters at the U.S.-Mexico border hit a record high at the end of 2023

What’s happening at the u.s.-mexico border in 7 charts, most americans are critical of government’s handling of situation at u.s.-mexico border, after surging in 2019, migrant apprehensions at u.s.-mexico border fell sharply in fiscal 2020, how border apprehensions, ice arrests and deportations have changed under trump, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

317 COVID-19 & Pandemic Essay Topics for Students

Although in May 2023, COVID-19 was declared to no longer be a public health emergency, it is still a global threat. We suggest a list of pandemic essay topics you can explore. In this collection of COVID-19 essay examples for students, we cover various dimensions of the pandemic, from origins to management and effects.

🦠 TOP 7 COVID-19 Essay Topics for Students

🏆 best pandemic essay topics, 🎓 interesting covid-19 essay topics for students, 👍 covid-19 essay examples for students, 💡 simple titles for covid-19 essay, 📌 more examples of covid-19 essays, ❓ pandemic research questions, ✍️ pandemic essay topics for college, 🔎 essay ideas on pandemic.

• Digital Technologies During the COVID-19 Pandemic
• Reflection on the COVID-19 Pandemic
• Leadership Approaches During the COVID-19 Pandemic
• Singapore Airlines’ Strategic Plan During the COVID-19 Pandemic
• Social Effects of the COVID-19 Pandemic
• Transactional Model of Stress and Coping and the Effect of the Pandemic on Nurses’ Well-being
• Online Learning During the Pandemic
• Walmart Digitalization in the Post-Pandemic Era At this moment, Walmart has to deal with technological advancement, customers’ interest in digitalization as a post-pandemic outcome, and unpredictable competitors’ moves.
• Tourism Industry During the Pandemic This paper assesses the impact of the COVID-19 pandemic on the supply and demand of tourism activities and consumer behavior.
• Social Changes After the Coronavirus Pandemic The global coronavirus pandemic is rapidly changing the economic, behavioural, and social aspects of people’s lives.
• The Impact of COVID-19 Pandemic The year 2019 will forever be engraved in many people’s hearts as the time when a virus known as the COVID-19 invaded almost all the sectors, thereby disrupting daily activities.
• Impact of the COVID-19 Pandemic on Air Canada The current project is going to discuss the impact of the COVID-19 pandemic on Air Canada and provide a PESTEL analysis of the organization.
• Zoom Video Communications During Covid-19 Pandemics The case study shows that Zoom company has become one of the most preferred brands in this industry since the COVID-19 pandemic because of its unique products.
• The Covid-19 Pandemic Impact on the Family Dynamic The problem threatened children’s mental and physical health, further exacerbated by inadequate access to welfare for those living in poverty.
• The Covid-19 Pandemic’s Influence on Socialization The recent COVID-19 pandemic has represented the topic of secondary socialization, unearthed the true extent of financial and social inequality across the world.
• The Covid-19 Pandemic Analysis Coronavirus, or Covid-19, is a contagious virus that began in December 2019. It causes an infection on the upper throat, sinuses, and nose.
• Pandemic Effects on Churches and Families Both churches and families appreciate those moments when they can be together, as it is often taken for granted pre-Covid 19.
• The COVID-19 Pandemic: Economic Impacts This paper aims to find the economic impacts of the coronavirus by exploring current financial status in the United States and around the world.
• Multinational Companies in a Post-Pandemic World As MNCs are major employers, it is important to determine their prospects to operate in the post-pandemic world of 2022.
• Pandemics in History Black Death, smallpox, Spanish flu were one of the most lethal and impactful pandemics. This paper describes the origin of these three outbreaks and analyses social consequences.
• The Impact of the COVID-19 Pandemic on the Standard Chartered Bank This paper will explore the impact that the COVID-19 pandemic had on the Standard Chartered bank, the development of technology, and its influence on human resource management.
• Tourism Sustainability After COVID-19 Pandemic This essay will discuss how the COVID-19 pandemic has influenced the sustainability sector of the tourism industry.
• Public Health: The Issue of HIV/AIDS Pandemic The public is involved in the prevention of HIV through the enhancement of public awareness. Advertisements that show prevention measures should be made for the public.
• COVID-19 Pandemic and New Parenthood This paper aims to explain the impact of COVID-19 on the breastfeeding process, the psychological well-being of new mothers, and the type of support necessary.
• Post-Pandemic Work Environment The COVID-19 pandemic has changed the way people approach work because the majority of companies had to transition to remote work.
• Impact of the Coronavirus Pandemic on the Global Economy The paper is aimed to overview the Coronavirus pandemic’s characteristics and analyze the outcomes of the disease outbreak within major economic spheres.
• Pre-pandemic and Pandemic Consumer Behavior The pandemic of COVID-19 has had a noticeable influence on consumer behavior around the globe that will most probably be long-term.
• Leadership and Management During COVID-19 Pandemic The current leadership framework that lifts a substantial amount of responsibility from the staff might help them feel relieved, yet will reduce the efficacy of their performance.
• Managerial Accounting in the COVID-19 Pandemic Any company or an organization with a dream of succeeding in the world of business should consider managerial accounting as a critical element of propelling its objectives.
• Impact of COVID-19 Pandemics on the Environment The spread of the COVID-19 and the contingency prevention measures harm the environment, and it is urgent to solve problems like the growing volume of waste.
• Ethical Controversies During COVID-19 Pandemic Regulations The paper discusses the ethical controversies involving USAA and Shake Shack from moral and economic points of view.
• Organizational Culture After the COVID-19 Pandemic The paper provides a collection of summaries or excerpts from various research papers on the effects of the Covid-19 pandemic on corporate culture.
• Impact of the COVID-19 Pandemic on Human Well-Being The COVID-19 pandemic taught people to appreciate their social ties and health more and helped them reconsider the impact of social isolation on human well-being.
• Mental Health and COVID-19 Pandemic The Covid-19 pandemic is one of the biggest global challenges in the last 50 years. The virus has affected world economies, health, societal cohesion, and daily life.
• COVID-19 Pandemic’s Impact on Hospitals The novel coronavirus has impacted hospitals and healthcare facilities, leading to increased strain on limited available resources and increased outpatient visitations.
• COVID-19 Pandemic: Businesses Negotiation Strategies The use of negotiation strategies can help businesses to reduce losses and service interruptions during the COVID-19 pandemic, thus offering a significant competitive advantage.
• Consumer Behavior During the COVID-19 Pandemic The pandemic has affected consumers’ purchasing behaviour. People have been spending less money on items such as clothes, jewelry, shoes, electronic gadgets, and games.
• The COVID-19 Pandemic Impacts on the US This paper discusses some of the social, economic, and psychological impacts of the COVID-19 pandemic on the United States of America.
• Government Responses and Expectations During the Influenza Pandemic of 1918-1919
• The Great Influenza: The Story of the Deadliest Pandemic in History
• Preparing Your Finances for a Bird Flu Pandemic
• Teachers’ Emotion and Identity Work During a Pandemic
• Disease Risk and Fertility: Evidence From the HIV/Aids Pandemic
• Disruptive Innovation Can Prevent the Next Pandemic
• Potential Bird Flu Pandemic
• Mental Health and Coping in the Shadow of the COVID-19 Pandemic: The Israeli Case
• Bank Integration and Systemic Risk: Panacea or Pandemic
• HIV/Aids Pandemic and Women
• Child Abuse: The Pandemic
• Could Avian Flu A(H5N1) Become a Pandemic
• Novel Criteria for When and How to Exit a COVID-19 Pandemic Lockdown
• Nepal Flu Pandemic: Causes and Solutions
• Vaccine Prioritization for Effective Pandemic Response
• COVID-19 and the Brazilian Reality: The Role of Favelas in Combating the Pandemic
• Choosing Between Adaptation and Prevention With an Increasing Probability of a Pandemic
• Relationship Between World War I and the Influenza Pandemic
• Hazard Prevention, Death and Dignity During COVID-19 Pandemic in Italy
• The Possible Macroeconomic Impact on the UK of an Influenza Pandemic
• Dehumanization During the COVID-19 Pandemic
• Emotional, Behavioral, and Psychological Impact of the COVID-19 Pandemic
• Modeling Influenza Pandemic and Planning Food Distribution
• Pandemic, Quarantine, and Psychological Time
• Stigma and Discrimination During COVID-19 Pandemic
• Solid Organ Transplantation During the COVID-19 Pandemic
• Psychological and Behavioral Responses to the COVID-19 Pandemic in Greece
• Spasticity Treatment During COVID-19 Pandemic
• Mortality From the Influenza Pandemic of 1918-19 in Indonesia
• Preparing Your Business for a Bird Flu Pandemic
• “Pandemics Are Not War” by Wilkinson: Article Review In her article “Pandemics are not war,” Wilkinson writes about the use of war as a metaphor for pandemics. She argues that it is unfair to view pandemics as a force of terror.
• The Malaysian Workforce After the COVID-19 Pandemic This essay discusses the employee health and well-being issue prevalent among the Malaysian workforce after the COVID-19 pandemic in detail.
• Social Institutions: Impact of the COVID-19 Pandemic The purpose of this paper is to identify how the COVID-19 pandemic has revealed the problems of various social institutions, such as the economy and education.
• Cancel Culture Before and After the COVID-19 Pandemic The case study will analyze various academic studies with a social science focus and will assist in defining how the cancel culture has been shaped by the pandemic.
• Food and Beverage Plan: The COVID-19 Pandemic Influence The COVID-19 pandemic has affected many social spheres. The food and beverage industry is still in the conditions of many restraints and limitations.
• Effects of the Pandemic on Early Childhood Education and Children The pandemic has placed early childhood education at serious risk. The closing of learning institutions that provide young children with education is a threat to their potential growth.
• Impact of the Coronavirus Pandemic on Human Relations In the article, the author analyzes how the coronavirus pandemic has impacted his relationships with family and friends.
• The Effect of Global Pandemic on the Role of Sports in Our Lives The pandemic has changed the way I view sports and their meaning in people’s lives, and I no longer view sports as primal for people.
• Intimate Partner Violence in the Australian Media During the COVID-19 Pandemic The pandemic and people’s resulting uncertainty about jobs and health can have a range of negative psychological effects, thus making conflicts between partners more common.
• The Black Plague vs. the COVID-19 Pandemic The documentary History of the Black Death recounts a global pandemic during the Middle Ages that can somewhat be equated with the COVID-19 pandemic.
• Coronavirus Pandemic in Context of Existentialism Once humans can consider coronavirus from an existential viewpoint, they may take it easier, accepting the situation and not being overly nervous.
• Nutrition: Obesity Pandemic and Genetic Code The environment in which we access the food we consume has changed. Unhealthy foods are cheaper, and there is no motivation to eat healthily.
• Virtual Visit to Louvre During Covid-19 Pandemic Louvre is a famous museum, with millions of visitors each year. The museum has a virtual tour, which is a treat in the period of COVID-related restrictions.
• Observing Harmony in Our Life During Covid-19 Pandemic During the pandemic, there have been many reasons to reflect upon the essence of the never-ending sequence of challenges that form the sequence of our lives.
• The Sphere of Leadership: Impact of the COVID-19 Pandemic This research paper is aimed at evaluating the influence of the COVID-19 pandemic on the sphere of leadership.
• Relation Between the COVID-19 Pandemic and Depression The paper is to share an insight into the detrimental effects of the COVID-19 pandemic on the mental health of thousands of people and provide advice on how to reduce its impact.
• COVID-19 Pandemic: Preparing a Presentation The social science issue I work on is urgent for the audience as it is related to the recent COVID-19 pandemic and shares actual data about changes among social institutions.
• Durkheim: Pandemic and Functionalism Durkheim defined the concept of division of labor as follows: “a way of investigating the moral consequences of the growing complexity within modern societies”.
• Covid-19 Pandemic Effect on the Economy The COVID-19 pandemic had a profoundly detrimental consequence on the state of micro- and macroeconomic activity.
• The COVID-19 Pandemic: Human Response The most adequate and effective human response to COVID-19 is launching public information campaigns that contribute to most individuals’ understanding of the situation.
• Government-Funded Assistance Before and After Pandemic Social welfare and national insurance programs are the primary forms of public support aid in the United States. Incentives from social programs are associated with low salaries.
• The Effectiveness of the US in Response COVID-19 Pandemic The paper discusses the effectiveness of the US in response COVID-19 pandemic, the lessons learned from COVID-19, and whether the CDC played its role.
• Police Brutality During COVID-19 Pandemic In the United States, there has been a perceived and observed police injustice towards minority communities, especially Blacks.
• Risk Communication in Pandemic Prevention Effective structuring of risk communication in a way that the citizens get all relevant information about a disease outbreak can prevent a pandemic in the future.
• Economic Systems During the Pandemic Government-mandated national lockdowns restrict COVID-19 propagation and negatively affect the economy. Employees were unable to work during the shutdown.
• How Has the COVID-19 Pandemic Changed the Human Resource Landscape The paper states that the COVID-19 pandemic has changed the human resources landscape, such as staffing, working patterns, and workplaces globally.
• Healthcare Costs Affected by the COVID-19 Pandemic In all over the world, the COVID-19 pandemic led to a dramatic growth of national healthcare spending as the prevention and treatment required the implementation of new measures.
• The COVID-19 Pandemic: Public Health Policy The COVID-19 pandemic has caused numerous health challenges and made it vital for healthcare professionals and policymakers to introduce new effective measures.
• The COVID-19 Pandemic: Patient Care Problem The essay discusses the COVID-19 pandemic patient care problem and its effect on the hospital’s budget and the role of a nurse leader in mitigating the effects.
• Decision-Making in Nursing: Impact of the COVID-19 Pandemic This paper deals with the impact the COVID-19 pandemic has had on the ability of nurses to make sound decisions as to the wellbeing of patients in clinical settings.
• The COVID-19 Pandemic: Role of Leisure The COVID-19 pandemic has presented numerous health challenges, and leisure activities have played a significant role in combatting it.
• Managing Incremental Healthcare Costs in a Post Pandemic World India’s burgeoning medical tourism industry offers affordable, high-quality healthcare services and wellness options, attracting global visitors.
• Combating Ebola and Marburg Outbreaks Compared to the COVID-19 Pandemic Treatments for the Zaire Ebola virus and vaccines for COVID-19 have been developed. In combating these epidemics, governments must acquire the required resources.
• Childhood Obesity During the COVID-19 Pandemic While the COVID-19 pandemic elicited one of the worst prevalences of childhood obesity, determining its extent was a problem due to the lockdown.
• Changes in Demand and Supply During the Coronavirus Pandemic The paper explains that government measures to regulate prices, namely the creation of price ceilings, created shortages of essential and personal care products.
• Parenting in a Pandemic: Tips to Keep the Calm at Home The article ​“Parenting in a Pandemic: Tips to Keep the Calm at Home” provides a set of recommendations for parents regarding managing children’s behaviors during the pandemic.
• Leadership Response to COVID-19 Pandemic Outbreak The paper presents a healthcare leadership response plan to the COVID-19 pandemic outbreak. It identifies the issue’s urgency and the importance of effective leadership.
• MD Properties’ Project Evaluation During the COVID-19 Pandemic The purpose of the report was to evaluate the project implemented by MD Properties in 2021 to adapt to help operations during the COVID-19 pandemic.
• COVID-19: Considerations for Children and Families During the Pandemic
• Risk and Protective Factors in the COVID-19 Pandemic
• Psychosocial Support for Healthcare Workers During the COVID-19 Pandemic
• Community Strategy For Pandemic Influenza
• Combating the Pandemic COVID-19: Clinical Trials, Therapies, and Perspectives
• Disease and Fertility: Evidence From the 1918 Influenza Pandemic in Sweden
• Pharmaceutical Patents and the HIV/Aids Pandemic
• Gender-based Violence During COVID-19 Pandemic
• Physical Fitness and Exercise During the COVID-19 Pandemic
• Pandemic Perspective: Commonalities Between COVID-19 and Cardio-oncology
• The Successes and Failures of the Initial COVID-19 Pandemic Response in Romania
• Food Safety During and After the Era of COVID-19 Pandemic
• Spanish Flu 1918 Pandemic
• Fighting Strategies Against the Novel Coronavirus Pandemic: Impact on Global Economy
• Diabetes the 132 Billion Dollar Pandemic
• Novel Coronavirus (COVID-19) Pandemic: The Role of Printing Media in Asian Countries
• Spanish Flu Global Pandemic
• Federal Reserve System Vigilant for Flu Pandemic
• Ethics and Preparedness Planning for an Influenza Pandemic
• Cancer Patient Management Challenges During the COVID-19 Pandemic
• Gaussian Doubling Times and Reproduction Factors of the COVID-19 Pandemic Disease
• Revisiting the Global Overfat Pandemic
• The COVID-19 Pandemic and Intelligence Communication in the United States
• Pregnancy During the Global COVID-19 Pandemic
• What Caused the Aids Pandemic?
• Radiation-induced Lymphopenia Beyond the COVID-19 Pandemic
• Exercise Frequency and Subjective Well-Being During COVID-19 Pandemic
• Challenges for Drug Repurposing in the COVID-19 Pandemic Era
• Flexible Teaching and Learning Modalities in Undergraduate Science Amid the COVID-19 Pandemic
• The Great Influenza Pandemic Was the Worse Pandemic That Occurs During the First World War
• Effects Women Have Faced During the COVID-19 Pandemic Globally The essay discusses the challenges women face in maintaining their economic security, juggling caregiving responsibilities, and coping with job losses and business closures.
• The Covid-19 Pandemic Impact on Business The pandemic significantly negatively influenced society and the global economy. The pandemic had a massive influence on economics, enterprises, and labor supply.
• Social Changes Due to the COVID-19 Pandemic The COVID-2019 pandemic has affected all areas of society, and from the experience gained, people should draw the appropriate conclusions in order to avoid this in the future.
• Discussion: Supply Chain Management and Pandemic Although the author was aware of the devastating impact of COVID-19 on the global supply chain, Ellyatt (2021) provides a more in-depth insight into this problem.
• Organizational Culture After the COVID-19 Pandemic The COVID-19 outbreak and its consequences led to the necessity to adjust to new working conditions and make corporate culture more flexible.
• Hotel Brands in the Post-Pandemic Era Strong hotel brands are fitter for the recovery after the COVID-19 pandemic and have more opportunities to attract new consumers and keep loyal ones.
• Domestic Violence in Melbourne: Impact of Unemployment Due to Pandemic Restrictions The purpose of this paper is to analyze to what extent does unemployment due to pandemic restrictions impact domestic violence against women in Melbourne.
• The Role of Digitalization in Supporting SMEs During the COVID-19 Pandemic This article analyzes the impact of the COVID-19 pandemic on SMEs and retailers, focusing on the organizational culture of retail businesses and their responses to the crisis.
• Policy Brief: Access to Education After the Pandemic The After-Hours Academy is a business that aims to provide learners from underserved communities with resources to improve their online education.
• The US Government Pandemic Initiatives In order to address the negative effects of the COVID-19 pandemic, governments worldwide, including in the United States, designed special initiatives to help companies.
• The 1918 Pandemic Representation The 1918 pandemic caused by the flu influenza led to the death of more than 50 million people and was believed to be one of the tremendous diseases in history.
• Struggles Families Encounter During Pandemic Since late 2019, the coronavirus pandemic has expanded far and quickly, wreaking havoc on countless families worldwide.
• The Impact of the COVID-19 Pandemic on Oceania It is necessary to analyze exactly how the pandemic affected the remote states of the Pacific Ocean and the fisheries in particular.
• The Impact of the COVID-19 Pandemic on Intimate Partner Violence in the US The safety measures implemented by the U.S. government in order to prevent the spread of coronavirus resulted in increased intimate partner violence in the country.
• The Impact of the COVID-19 Pandemic on Sibling Violence The problem of domestic abuse has been extensively studied by researchers worldwide, and one of the main forms of the phenomenon is sibling violence.
• Job Losses as a Result of the Pandemic Macroeconomics examines the performance of the economy in general, as such, the issue of job losses demonstrates how the economy of countries was affected by Covid-19.
• Stress in Pregnant Women Due to COVID-19 Pandemic Pregnancy is a particularly crucial time for the mental health of a woman. The high levels of stress have been linked to exposure to the pandemic.
• Issues of Working With People During the Pandemic Communication is essential when de-escalating a crisis. It is critical that they feel understood, so they need to pay close attention to them.
• The Rental Housing Market Challenges During the COVID Pandemic The policy of freezing the rental price and setting the bar for a monthly fee, as in a German city, can significantly improve the situation in Istanbul.
• How the COVID-19 Pandemic Is Changing the Economy World Health Organization characterized the illness as a pandemic on 11th March 2020, resulting in 3 million cases and the demise of 207,973 people.
• The COVID-19 Pandemic’s Social Impact The authors of the article examine the impact of COVID-19 on the psychological and social conditions of the population.
• Air Canada: History, Profit, Pandemic, and Future Air Canada delivers not only people but also cargo all over the world, but, unfortunately, it took a full two years for the company to adapt to the pandemic.
• Utilitarianism and PR During the Pandemic The principle of utilitarianism in the PR sphere contradicts the modern ethical paradigm because it cannot fully provide the ability to make decisions.
• Vaccination Issue Concerning the COVID-19 Pandemic This paper discusses the current vaccination issue concerning the COVID-19 pandemic. Large numbers of patients worldwide refuse vaccines.
• The COVID-19 Pandemic and the Black Plaque This paper discusses the social, economic, and political factors contributing to COVID-19 in the domestic and international spheres and connects COVID-19 and the Black Plague.
• Modeling the Impact of the COVID-19 Pandemic Coronavirus has taken a substantial toll on people worldwide. Being only a year after the eruption of the virus from Wuhan, its effects have been felt globally.
• Addressing Economic Inequality: The Pandemic Challenge Economic inequality continues to be relevant to modern society, with the full range of human rights being available only to the wealthy minority.
• Pandemic Coverage: Omicron Issues The news media provided trustworthy information surrounding pandemic-related developments that had transpired but proved inefficient in making prognoses.
• Economic Inequality and Pandemic Challenge The most vulnerable populations were affected by the coronavirus pandemic because they often could not access economic and public health resources to meet their needs.
• Influenza (H2N1) vs. COVID-19 Pandemic COVID-19 and H2N1 pandemic has impacted the lives of many people. Both pandemics have some similarities and differences, and each has a particular significance.
• The Issue of the Opioid Pandemic in the USA The efforts at addressing the issue of an opioid pandemic have been quite numerous, yet the results that they have yielded cannot be described as stellar.
• COVID-19 Pandemic: Social Media Response by the American Government Using social media to address the public on COVID-19, President Biden and his vice have developed a seven-point plan to help combat the pandemic.
• Pandemic Challenge and Economic Inequality The coronavirus pandemic has presented two significant challenges for American society: public health and economic crises.
• The Impact of the COVID-19 Pandemic on the International Trading The coronavirus pandemic has created new tough barriers to globalization and trade: the shutdown of production and the borders of leading countries and economic groups.
• Production and Growth During the Pandemic: A Case of U.S. Manufacturing By recognizing the factors that shape the production process, U.S. manufacturers have managed to continue delivering solid performance despite the effects of the coronavirus.
• “And the Band Played On” During the AIDS Pandemic The movie “And the Band Played On” touches on different prevalent issues during the AIDS pandemic that affected the world in the 1980s.
• Planning in a Post-Pandemic World With the need for new, stricter health regulations in the workplace for a safer internal environment in the office come limitations on the number of persons of staff present.
• Pandemic in Seurat’s “A Sunday Afternoon on the Island of la Grande Jatte” The current paper includes reflecting on the pandemic through the lens of Seurat’s “A Sunday Afternoon on the Island of La Grande Jatte”.
• Could Avian Flu AH5N1 Become a Pandemic?
• Does the Coronavirus (COVID-19) Pandemic Call for a New Model of Older People Care?
• How Can the COVID-19 Pandemic Lead To Positive Changes in Urology Residency?
• How Should HIV/Aids Pandemic Be Addressed?
• What Is the Potential for Avian Influenza to Cause Another Worldwide Pandemic?
• What Is the Impact of Pandemic COVID-19 on Education in India?
• What Are the Regulatory Challenges for Drug Repurposing During the COVID-19 Pandemic?
• What Were the Successes and Failures of the Initial COVID-19 Pandemic Response in Romania?
• Why Obesity Is the New Global Pandemic of 21st Century?
• What Is the Possible Macroeconomic Impact on the UK of an Influenza Pandemic?
• How Financial Markets Lived Under the Global Pandemic of COVID-19?
• What Are the Measures of Ecology and Economics for Pandemic Prevention?
• Are Women Publishing Less During the Pandemic?
• What Is the Impact of COVID-19’s Pandemic on the Economy of Indonesia?
• Which Interventions Work Best in a Pandemic?
• Why Community Participation Is Crucial in a Pandemic?
• How to Prepare Business for a Post-pandemic World?
• What Are the Strategies for Mitigating an Influenza Pandemic?
• What Are the Origins of HIV and the Aids Pandemic?
• How to Predict and Prevent the Next Pandemic Zoonosis?
• How Did COVID‐19 Pandemic Show Cricial Cybersecurity Issues?
• What Are the Best Practices for Implementing Remote Learning During a Pandemic?
• What Were the Ecological Consequences of a Pandemic?
• How to Manage the Effectiveness of E-Commerce Platforms in a Pandemic?
• What Are the Internal and External Effects of Social Distancing in a Pandemic?
• Police Killing Black People in a Pandemic Police violence as a network of brutal measures is sponsored by the government that gives the police officers permission to treat black people with disdain.
• Racial Discrimination in the Industry of Face Masks During the COVID-19 Pandemic This research, done in an industry that produces face masks, provides a clear image of racism during the coronavirus pandemic period.
• American Pandemics From Columbus to Coronavirus The decisions made by previous generations of Americans during epidemics led to the development of structural racism and class segregation.
• The COVID-19 Pandemic’s Impact on the Airline Industry The main objective of the paper was to provide evidence-based coverage of the impact of the Covid-19 pandemic on airline operations around the world.
• Pandemic-Related Changes in Consumer Behavior The COVID-19 pandemic has affected consumer behavior around the globe so considerably that new trends have emerged that are mostly based on seeking stability.
• United States Economy’s Outlook After Pandemic The United States has shown signs of a rebound after the Covid-19 pandemic through the rising GDP and the low unemployment rates witnessed in the country.
• Pandemic’s Impact on Mental Health & Substance and Alcohol Abuse While substance use disorder can impose mental health challenges on those who consume drugs, COVID-19 affects the psychology of all humankind.
• The US Stock Market Affected by the COVID-19 Pandemic Despite the terrible effects that the coronavirus has had on the stock market in the United States, it is clear that the country has gained a great deal from the adverse effects.
• COVID-19 Pandemic in Media: Agenda Setting Theory For the analysis, the currently gaining attention theory about the laboratory origin of the virus was chosen, as well as its coverage in authoritative publications.
• The H3N2 Virus Pandemics of 1968 The H3N2 virus contained two genes derived from the six genes from the A(H2N2) virus, associated with the 1957 H2N2 pandemic.
• The COVID-19 Pandemic and Labor Market Dynamics The labor market dynamics of the COVID-19 recession in the United States are studied using a search-and-matching model incorporating temporary unemployment.
• Recovery the Post Pandemic World The paper briefly explains what sort of recovery the post-pandemic world will likely experience and how Ireland is positioned to cope or change tact.
• The Influence of the COVID-19 Pandemic on the Housing Market in Singapore Despite the COVID-19 pandemic, which has caused various economies around the globe to fumble and struggle, the housing market in Singapore tends to remain healthy.
• Impact of COVID-19 Pandemic on the African American Communities This paper analyzes how the COVID-19 pandemic affected the economic aspect of the African American communities. A female and two males were interviewed.
• The COVID-19 Pandemic and Its Effects Worldwide Covid-19 has remained a threat in many countries in the last two years. Numerous restrictions and precautions have been implemented in various nations.
• COVID-19 and Playing Sports During a Pandemic The review focuses on three significant sports areas under the conditions of a pandemic: health, commercialism, and structural aspects.
• COVID-19 Pandemic and Valuable Cargo The COVID-19 pandemic has played a significant role in changing logistics, with the supply chain playing a more critical role than ever before.
• Telehealth in the Pandemic: Benefits & Limitations Despite the benefits of telehealth during the pandemic period, the older population still has reservations about the suitability and efficacy of such technologies in the long run.
• Review of “For Millions, the Pandemic Is Far From Over” Article The article by Doheny, presented by the reputable healthcare source Medscape, examines the challenges of immunocompromised Americans.
• The COVID-19 Pandemic Impact on Society COVID-19 has disrupted daily life and slowed the global economy. In addition, thousands of people have been affected by this pandemic, and are either sick or dying.
• Extraversion & Social Connectedness for Life Satisfaction During the Pandemic This laboratory report critically examines the effects of strict isolation and social distancing on perceptions of self-satisfaction.
• Older Adults Surviving the COVID-19 Pandemic: The Mental Health Benefits of Physical Activity The aim of this paper is to identify the effect of physical activity on mental health among older adults during the COVID-19 pandemic.
• Virtual Teams’ Adaptation to the Conditions of the COVID-19 Pandemic Virtual teams’ adaptation to the conditions of the COVID-19 pandemic happened through forced utilization of technology to establish effective communication.
• The Dabbawalas and the COVID-19 Pandemic The global COVID-19 pandemic cannot go unnoticed for the dabbawalas, which is a system of lunchbox delivery and return services for India’s employees.
• Global Pandemic of COVID-19 From an Epidemiological Perspective The epidemiological perspective of the COVID-19 pandemic requires studying the statistical data for identifying patterns that could be addressed or eliminated.
• Supply Chain Management Challenges Amid the COVID-19 Pandemic The increasing number of suppliers and business continuity risks must be considered to find relevant solutions to the Kuwaiti supply chain management problem.
• The COVID-19 Pandemic’s Impact on Australia This work will focus on discussing some of the considerations necessary for the Australian business to start its operation in a new market environment during COVID-19.
• Long-Term Changes in Information Technology During the Pandemic of COVID-19 The outbreak of the COVID-19 in China is not only destructing the global economy but it can also have a positive effect on the development of the IT industry.
• Covid-19 Pandemic-Related Macroeconomic Issues COVID-19 fueled many macroeconomic issues. The first is high inflation which increased the living costs and pressure on low-income earners.
• Texas Judiciary During the COVID-19 Pandemic The current paper indicates that the main issues faced by the Texas justice system and state judges are caused by the COVID-19 pandemic.
• The COVID-19 Pandemic Has Brought Us Too Close Together The resources presented in the articles depict a new reality where violence and riots occur due to a depressed populace who can’t stand any injustice.
• Consumer Behavior: Impact of the COVID-19 Pandemic Consumers come out of COVID-19 with very different habits, and the main challenge for businesses, both small and large, is to find an approach in the new environment.
• How the Corona Virus-19 Pandemic Affected Society This paper discusses the Corona Virus-19 effect on society’s stratification and social classes, politics, families and marriages, and problems in education that students faced.
• Healthcare Policy Influences: COVID-19 Pandemic The research indicates that the impactful aspect of the economy of a nation became the most prominent during the COVID-19 pandemic.
• Built Environment and Pandemics Healthy built environments have services and resources that contribute to the physical, mental, and social wellbeing of the people who occupy it.
• Hate Crimes Against Asian Americans During the Pandemic An outbreak of hate crimes targeting Asian Americans after the outbreak of the pandemic has led to thousands of violent episodes against members of the group.
• Hand Sanitizers in COVID-19 Pandemic: Pros and Cons The paper states that hand sanitizers are indeed associated with controversial aspects and have both positive and negative properties.
• The Story of Sam, OCD, and the COVID Pandemic Her name is Sam, short for Samantha; you may not tell by looking at her, but she has a mental condition called obsessive-compulsive disorder.
• Parents and Children’s E-Safety Education During the Pandemic
• Domestic Violence During COVID-19 Pandemic
• Arguments Against Masks During Pandemic and Personal Freedom
• White and Black People in USA During COVID-19 Pandemic
• Psychological Effects COVID-19 Pandemic Leading to Hospital Nursing Shortage
• Poor Staff Management During the Pandemic
• Economic Predictions on Recovery After COVID-19 Pandemic Shock
• Tourism and Sustainable Development During the COVID-19 Pandemic
• Healthcare for Underserved Communities During Covid-19 Pandemic
• Preparing a Child for School During COVID Pandemic
• Restaurant Business During The Pandemic
• US Actions Concerning COVID-19 Pandemic
• The Effect of the COVID-19 Pandemic on Businesses
• Can Coronavirus Pandemic Lead to World War III?
• Poor Management & Care Quality During the COVID-19 Pandemic
• The COVID-19 Pandemic in US and World History
• Comparison of How Communities React to Plagues and COVID-19 Pandemic
• Social Solidarity During the Pandemic
• The COVID-19 Pandemic Organizational Risk Management Strategies
• Global Society: Before and After The Coronavirus Pandemic
• The Covid-19 Pandemic of 2019-2021
• Autoethnography: The COVID-19 Pandemic
• VA Telehealth During the COVID-19 Pandemic: Expansion and Impact
• Mental Health During the Pandemic: Research Design, Steps, and Approach
• Physical Activity Impact on Psychological Health During COVID-19 Pandemic
• Public Policy Meeting: “VA Telehealth During the COVID-19 Pandemic”
• Existence of God in Times of Covid-19 Pandemic
• How Can Irish Funeral Traditions Help the Bereaved People Cope with Losses during the Pandemic?
• Children and the COVID-19 Pandemic
• Covid-19 Pandemic and Mental Health of American Population
• Key Takeaways from the Coronavirus Pandemic
• Racial Inequalities in the Context of Pandemic Vaccination
• Healthcare Rationing During a Pandemic
• Pandemics & Biothreats and Governmental Responses
• Labor Market Developments During the Covid-19 Pandemic
• Influenza Pandemic Outbreak Analysis
• Streaming Service for the Elderly During the COVID-19 Pandemic
• Picnics Become Popular Around the Globe During Pandemics

🌶️ Hot Pandemic Ideas to Write about

• School Closure During Influenza Pandemic
• Influenza Pandemic Outbreak Overview
• Changing Health Behavior in Current Pandemic Situation
• The Impact of COVID-19 Pandemic on the Community of Charleston, South Carolina
• Mental Health Buring a COVID-19 Pandemic
• Is the Pandemic Beneficial?: Argument with an Opossum
• Job Satisfaction Levels During the COVID-19 Pandemic
• Christianity and the COVID-19 Pandemic
• COVID-19 Pandemic: Economic Factors and Consequences
• Florida Administration’s Response to the Coronavirus Pandemic
• The COVID-19 Pandemic Impact on Social Values
• City Planning and Pandemics: Efficient Approach
• COVID-19 Pandemic’s Impact on the Environment
• Nature Relatedness and Well-Being during COVID-19 Pandemic
• COVID-19 Pandemic: What We Can Learn From the Past?
• COVID-19 Pandemic and a Globalized Economy
• Psychonomics of Consumers During the covid19 Pandemic
• Social Barriers During the COVID-19 Pandemic
• How the Pandemic Has Worsened Opioid Addition
• The Impact of the Worldwide COVID-19 Pandemic on Essential Social Values
• Project Management in Healthcare During the COVID-19 Pandemic
• The Sports Industry During the Covid-19 Pandemic
• Ethical Perspective on Pandemics
• Airline Labor Relations During the COVID-19 Pandemic
• Mitigating the Impact of the Novel Coronavirus Pandemic
• The Company’s Exit from the Crisis in a Pandemic
• Employees Retention During COVID-19 Pandemic
• Pandemics and Epidemics that Changed the World
• Streaming Service and Elderly During COVID-19 Pandemic
• Hoarding and Opportunistic Behavior during COVID-19 Pandemics
• Racist Assaults Against Asians and Coronavirus Pandemic
• Australian Freight Companies’ Ethics During the COVID-19 Pandemics
• Pandemic and Its Aftermath Impact
• Budgetary Change: Unstable Situation Due to the Pandemic
• City Planning and Pandemic: Efficient Approach
• Psychological Effects of Pandemic Control Measures
• Global Pandemic Issues: Prevention of Infection and Transmission of COVID-19
• “Senate HELP Hearing on Coronavirus Responses and Future Pandemic Preparedness”: An Overview
• The Coronavirus Pandemic: Detergents Against the Germs
• AIDS Pandemic: Impact on Human Health
• Negative Impact of the 2020 COVID Pandemic on World Industries
• 2009 H1N1 Flu Pandemic, Vaccination and Rates

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StudyCorgi. (2022, March 1). 317 COVID-19 & Pandemic Essay Topics for Students. https://studycorgi.com/ideas/pandemic-essay-topics/

"317 COVID-19 & Pandemic Essay Topics for Students." StudyCorgi , 1 Mar. 2022, studycorgi.com/ideas/pandemic-essay-topics/.

StudyCorgi . (2022) '317 COVID-19 & Pandemic Essay Topics for Students'. 1 March.

1. StudyCorgi . "317 COVID-19 & Pandemic Essay Topics for Students." March 1, 2022. https://studycorgi.com/ideas/pandemic-essay-topics/.

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StudyCorgi . "317 COVID-19 & Pandemic Essay Topics for Students." March 1, 2022. https://studycorgi.com/ideas/pandemic-essay-topics/.

StudyCorgi . 2022. "317 COVID-19 & Pandemic Essay Topics for Students." March 1, 2022. https://studycorgi.com/ideas/pandemic-essay-topics/.

These essay examples and topics on Pandemic were carefully selected by the StudyCorgi editorial team. They meet our highest standards in terms of grammar, punctuation, style, and fact accuracy. Please ensure you properly reference the materials if you’re using them to write your assignment.

This essay topic collection was updated on January 22, 2024 .