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A systematic review on the impacts of Covid‐19 on work: Contributions and a path forward from the perspectives of ergonomics and psychodynamics of work

Tiago f. a. c. sigahi.

1 Department of Production Engineering, University of São Paulo, São Paulo SP, Brazil

Bruno C. Kawasaki

2 Department of Psychology, Federal University of Paraíba, Cidade Universitária, João Pessoa PB, Brazil

Sandra N. Morioka

3 Department of Production Engineering, Federal University of Paraíba, Cidade Universitária, João Pessoa PB, Brazil

Associated Data

The data that supports the findings of this study are available in the supplementary material of this article.

Work is a major issue in the discussions on the Covid‐19 pandemic, whose consequences impair the capacities of workers at all organizational levels and impose unexpected challenges on managers. Nevertheless, the scientific literature still lacks an overview of how researchers have been covering the issue. This article presents a systematic review to investigate the impact of Covid‐19 on work and workers of all occupations, reveal research gaps, and help managers to adapt to organizations amid the pandemic. This review is based on a sample of 258 papers from Web of Science and Scopus databases. Quantitative and qualitative analysis indicated a vast majority of studies focused on frontline healthcare workers and a lack of empirical investigation on managers' work. We show how literature has been addressing different aspects of work (e.g., workers' health, working conditions, procedures, protection equipment, remote working, etc.) in the various economic sectors. We discuss the results in light of ergonomics and psychodynamics of work, two disciplines that conceive work and organization as intimately connected, and that can assist managers in meeting the difficulties brought by the pandemic. We highlight that considering the construction of health, interindividual variability, subjective relation to work, supportive workplace environment, and organizational and individual capabilities can play a key role in successfully adapting and transforming organizations in the current scenario.

1. INTRODUCTION

The Covid‐19 pandemic has raised questions on how human life is and should be organized. Organizations and societies certainly have had their lives radically and rapidly transformed, whereas the effects of the pandemic crisis in the long term are uncertain. Studies in various fields of management have been trying to understand the impact of this crisis on organizations. The literature reveals diverse transformations in business models (Ritter & Pedersen, 2020 ), innovation strategies (Chesbrough, 2020 ), corporate social responsibility, marketing (He & Harris, 2020 ), value chains (Verbeke, 2020 ), supply chains (Ivanov, 2020 ), consumer behavior (Sheth, 2020 ), and management education (Beech & Anseel, 2020 ; Brammer & Clark, 2020 ).

One aspect that permeates the aforementioned transformations, but deserves more scholarly attention, is work—including managers' work. The centrality of work in the construction of workers' health, social relations, and organizations (Dejours & Deranty, 2010 ) points to the need to advance in the subject. The impact of Covid‐19 on work and workers is diverse. After its outbreak, some of the ongoing transformations, such as the digitalization of work and the growing prevalence of mental health disorders, have accelerated. Also, novel discussions emerged on topics, including changes in work procedures, personal protection equipment (PPE), infection control strategies, behavior, gender, and ethics. In the scholarly literature, however, there is still much to explore on the impact of Covid‐19 on work and workers, and the implications for management. In one of the few articles on this subject, Carnevale and Hatak ( 2020 ) explore both challenges and opportunities that the pandemic represents to human resources management (HRM), and claim that management scholars should coordinate research on it. In particular, the authors affirm the importance of integrating different disciplines so that HRM issues can be addressed in an integrative way. As Donthu and Gustafsson ( 2020 , p. 284) state, Covid‐19 is “a sharp reminder that pandemics, like other rarely occurring catastrophes, have happened in the past and will continue to happen in the future.”

This article, therefore, has the following objectives: (1) to review the current academic knowledge of the impact of Covid‐19 on work and workers, thus revealing research gaps and managerial challenges; and (2) to help organizations understand how to adapt work while remaining competitive. To achieve the objectives, we conducted a systematic literature review based on scientific databases and discussed our findings based on concepts of ergonomics and psychodynamics of work (PDW), thus complementing Carnevale and Hatak ( 2020 ). Both disciplines can contribute to the field of management by promoting organizational improvements that are less prescriptive (top‐down approach) and more communicative (bottom‐up approach), in line with the need to manage broad organizational changes imposed by the pandemic crisis.

On the one hand, ergonomics investigates the relationships between workers and other components of a system, such as tools, equipment, and technologies. Interventions in ergonomics aim to enhance human wellbeing and system performance as well (International Ergonomics Association [IEA], 2020 ). On the other hand, PDW investigates the relationship between work, worker's health, and suffering associated with work organization. In PDW, interventions afford spaces of discussion where workers can rely on each other to disclose and debate aspects of work that usually remain silenced, for example, fears, constraints, and difficulties (Dashtipour & Vidaillet, 2017 ; Dejours, 1992 , 2012 ). Both disciplines presume the centrality of work in organizations (Dejours & Deranty, 2010 ) and the importance of workers' involvement and participation (Bolis et al., 2012 ; Dejours, 2009 ) so that organizations can better deal with intrinsic and extrinsic variability in the production of goods or services (Falzon, 2004 ). In the context of drastic changes, such as the Covid‐19 pandemic, considering workers and their subjectivity can be decisive for organizations. Workers at all organizational levels can contribute with their knowledge, skills, and creativity to help organizations restructure and adapt to new realities. Also, by understanding how work is being affected by the pandemic, leaders can help their organizations respond more effectively in the short term and be better prepared in the long term.

Systematic literature reviews are based on objective, rigorous criteria that allow transparency and replicability by other researchers. In this sense, systematic reviews differ from literature reviews, which traditionally have author bias (Tranfield et al., 2003 ). Our systematic literature review thus comprised three main phases: definition of the sample of publications to be analyzed; descriptive and network analysis; and qualitative classification and analysis. Next, each phase is described.

2.1. Definition of the sample

The definition of the sample of the systematic literature review began with a search in ISI Web of Science and Scopus databases for publications fitting the following conditions: (i) directly related to Covid‐19: search for (covid‐19 OR coronavirus OR sars‐cov) in the title, abstract, or keywords; AND (ii) work‐related issues: search for (work* OR job OR labor OR labor) in the title or keywords. In addition, only documents written in English, published in 2020, and classified as “article” or “review” were selected. The search was conducted on July 23, 2020.

The selection process of articles was conducted in steps as recommended by the PRISMA protocol (Moher et al., 2015 ) (Figure ​ (Figure1). 1 ). After removing duplicate records, an initial screening based on article titles and abstracts was performed to eliminate articles in which Covid‐19 and work or workers were not the core topic.

Selection process of the articles

In the eligibility step, the following exclusion criteria were applied:

• articles in which work or workers were not the core topic;
• articles focused on minimizing the spread of Covid‐19 that do not result in organizational or work process changes (e.g., testing workers for infection);
• articles based on opinions on Covid‐19 that have no clear impact on work;
• articles with religious biases;
• articles focused on public policies or initiatives that have no clear impact on work;
• articles consisting of tributes to a particular professional category;
• articles analyzing specific procedures without mentioning the impact on work; and 
• research articles whose results were not submitted to a peer‐review process.

To reduce the risk of bias, screening and eligibility steps were conducted by two researchers, who independently evaluated the articles. In the screening step, only articles with both researchers' rejection were excluded. In case of divergence, the article was accepted for the following step. In the eligibility step, the two researchers diverged on 47 articles, which was solved by a discussion with a third researcher. The final sample consisted of 258 articles (see Supporting Information Appendix A).

2.2. Descriptive and network analysis

In the second phase, the sample was analyzed based on its metadata. The most frequent journals and the most cited papers were identified with MS Excel. Then, the journal co‐citation and keyword networks were generated with VOSviewer software (van Eck & Waltman, 2010 ).

Each type of information was analyzed to obtain an initial overview of the sample (see Section 3.1 ). The keyword network was particularly relevant to identify thematic clusters, which also concerns the next research phase dedicated to categorization and qualitative analysis of the articles.

2.3. Classification and qualitative content analysis

The third phase of the systematic review was performed to investigate the content of the articles. Two researchers read mainly the abstract and discussion sections and independently organized the articles on an MS Excel sheet. The content of each paper was thus extracted and categorized in two dimensions: economic sector and aspects of work addressed (e.g., effects on workers' health, working conditions, etc.). The definition of the aspects of work was based on keyword network analysis (developed in the previous phase) and qualitative analysis of the papers. Divergences on how to define them were solved by reaching a consensus among the researchers.

The classification in two dimensions allowed to identify groups of articles discussing similar topics. By extracting and gathering information from each group, it was possible to understand what has been published about the impact of Covid‐19 on work and workers (see Section 3.2 ). The results revealed research gaps and led to a discussion on how organizations can adapt work to protect workers amid the Covid‐19 pandemic.

3.1. Descriptive and network analysis

The main journals, that is, the ones with three or more articles in the sample, are listed in Table ​ Table1. 1 . Around 20% of the articles are concentrated in 6% (12 out of 189) of the journals. Journals in the field of health predominate, except for the Sustainability (Switzerland) journal, whose scope includes environmental, cultural, economic, and social sustainability. Furthermore, only nine articles from journals of business, administration, or economics are in the sample, indicating that the impact of Covid‐19 on work has been little explored in these fields.

Main journals of the sample

Table ​ Table2 2 lists the most cited articles in the sample. Since they were published in 2020, the high number of citations (according to the Scopus database) indicates that the topic is in evidence in the scientific literature. Only one of the articles in the list addresses the impact of Covid‐19 on the workforce in general (Zhang et al., 2020a); all others focus on healthcare workers (HCWs) concerning the following issues: mental health (Chew et al., 2020; Lai et al., 2020a; Lu et al, 2020; Shanafelt et al., 2020; Zhang et al., 2020b), changes in work organization (Forrester et al., 2020; Wong et al., 2020), respirators and PPE (Ranney et al., 2020; Bartoszko et al., 2020), contagion reduction strategies (Prem et al., 2020), and effects of school closure on workers' childcare obligations (Bayham & Fenichel, 2020).

Most cited articles in the sample

In the journal co‐citation network (Figure ​ (Figure2), 2 ), the nodes represent the journals cited by the articles in the sample. The strength of the connection between two nodes is proportional to how many times the two respective journals were co‐cited (i.e., cited together) by the articles in the sample, whereas the size of a node reflects how many times the respective journal was cited by the papers in the sample. Thus, the network highlights the main sources that have been consulted by researchers interested in work‐related issues in times of Covid‐19. The restriction to elaborate the network is that the journal has been cited at least 10 times, which resulted in a network with 36 nodes. Again, journals in the field of health predominate. Highlights include the New England Journal of Medicine , The Lancet , and JAMA ( Journal of American Medical Association ), but the network also shows journals with a wider scope, such as PLOS One , Nature , and Science . From an organizational point of view, it is worth mentioning the journal Sustainability ( Switzerland ). Journals on oncology are grouped in a separate yellow cluster (upper right region of Figure ​ Figure2), 2 ), thus suggesting this topic has been addressed rather separately from the others.

Journal co‐citation network

Figure ​ Figure3 3 shows the keyword network of the articles in the sample. Node sizes are proportional to how many times the respective keywords were cited by the articles. Two nodes are connected if the respective keywords were co‐cited, that is, mentioned by an article, and the strength of the connection between two nodes is proportional to how many times the respective keywords were co‐cited. The restriction to generate this network is that each keyword was cited at least twice, which resulted in 99 nodes. Since almost all articles of the sample cite Covid‐19 or its variations (e.g., pandemic, novel coronavirus) as keywords, these terms were excluded from the network to make it easier to visualize.

Keyword network

The network in Figure ​ Figure3 3 confirms the content of the most cited articles (Table ​ (Table2) 2 ) in the sense of showing a strong presence of studies on HCWs (node “hcw”), and mental health and related issues, for example, depression, stress, and anxiety (purple and yellow clusters, the lower left region of Figure ​ Figure3). 3 ). The topic, “changes in work procedures” (orange cluster, the upper region, including nodes “workflow” and “leadership”), seems to be linked to ethical issues at work. Respirators and PPE (nodes “ppe,” “masks,” “safety”) are represented by the pink and green clusters (right region). Contagion reduction strategies, previously identified in Table ​ Table2, 2 , are here verified in the red cluster (central right region, nodes “epidemiology,” and “infection control”) as well as in the brown cluster (bottom region, nodes linked to “knowledge” and “attitudes”). Effects on society and work are represented in the light blue and dark blue clusters (upper left region), which include remote working, telemedicine, academia, and flexible work. The keyword network analysis suggests that articles could be organized in two dimensions: economic sector (where the healthcare sector predominates) and aspects of work (e.g., mental health, work procedures, ethical issues, PPE).

3.2. Qualitative analysis: Literature content and gaps

The qualitative analysis of the sample allowed to categorize the articles in groups according to the dimensions “aspects of work” and “economic sector,” as shown in Table ​ Table3 3 .

Number of articles regarding the aspects of work and economic sectors addressed

Note : The same article can be classified in more than one aspect of work.

The groups of articles were analyzed with respect to content and literature gaps. Due to space limitation and size differences, some groups were analyzed separately and others together, as indicated by the boxes in Table ​ Table3. 3 . Only in the case of the health sector, the seven aspects of work were separately analyzed (Section 3.2.1 ). The education sector (Section 3.2.3 ) and other economic sectors (Section 3.2.3 ) were analyzed without explicit distinction between the aspects of work.

3.2.1. HCWs and healthcare organizations

In this section, we analyze the papers whose focus is HCWs. On the one hand, various professional categories have been considered by the literature, such as nurses (Duncan, 2020; Howarth et al., 2020), surgeons (Berardi et al., 2020; Ducournau et al., 2020), community health workers (Ballard et al., 2020; Bhaumik et al., 2020), psychologists (Geoffroy et al., 2020; McBride et al., 2020; Thompson & Kramer, 2020), etc. On the other hand, we have identified the opportunity for future research on other occupations existing in hospitals (e.g., attendants, security guards and cleaning professionals, administrators and executives, heads of teams or sectors); public servants and other professionals directly involved in public health crisis committees; and workers (including researchers) engaged in developing or producing drugs, vaccines, supplies, or equipment to fight Covid‐19. Next, the papers classified in the health sector are analyzed regarding different aspects of work.

Effects on workers' health

The effects on frontline HCWs' health, and especially mental health, have been widely addressed. Physical and emotional stress can compromise their performance during and after the pandemic, given the risk of posttraumatic stress disorder (Ornell et al., 2020).

In this group of articles, approximately half of them correspond to quantitative research related to epidemiological surveys. Editorials and expert commentaries represent about a third of the articles and have mainly addressed workers' mental health. The remaining articles are action research on the development of psychological support systems for HCWs, and qualitative empirical research on frontline work in hospitals.

The quantitative research papers concentrate on measuring the physical and psychological symptoms in frontline HCWs, thereby evidencing this category has been especially vulnerable. The symptoms include fatigue, headache, stress, irritability, anxiety, fear, depression, burnout, suicidal ideation, insomnia, and eating and mental disorders. Prolonged use of masks can compromise work performance as it contributes to headaches (Ong et al., 2020) and skin reactions (Hu et al., 2020).

While most literature on HCWs' health has been limited to describing their psychological symptoms, some studies have gone further, aiming to identify risk or protective factors too. The main mental health risk factors for HCWs are pre‐existing medical conditions; being younger; having less professional experience; having dependent children; having infected family members; being quarantined for a long period of time; suffering social stigma; being exposed to infected patients or colleagues; poor workplace infection control; lack of practical or organizational support; lack of PPE or not feeling safe with the one provided; and work overload (Kisely et al., 2020; Mhango et al., 2020; Sharif et al., 2020). Conversely, mental health protective factors include: having moderate rather than extreme concerns regarding family members; clear communication among hospital staff; practical and psychological support; adequate rest; and access to appropriate PPE (Kisely et al., 2020; Sharif et al., 2020). Hence, we note that among the risk and protective factors, there are aspects related to organizational support under the direct influence of healthcare managers.

Qualitative research in this group of articles is based on interviews and investigates the day‐to‐day and difficulties of frontline HCWs. In general, it corroborates that the risk and protective factors for the mental health of HCWs are directly associated with the level of organizational support. Other sources of anxiety identified by qualitative studies are: feeling helpless in the face of insufficient personnel, equipment, or materials; drastic changes in team composition and work organization, thus having to learn new tasks; social stigma due to daily contact with infected patients; and lack of reliable, clear, and updated information. Often there is insufficient information on the following issues: protocols to treat Covid‐19; leaders, command structure, and situation of patients in the hospital; and evolution of the pandemic in the local and national contexts (Fawaz & Samaha, 2020; Liu et al., 2020; Shanafelt et al., 2020; Sun et al., 2020).

Among frontline HCWs, women are a group at risk for various reasons. Nurses are mostly women having to perform tasks that require a high level of contact with patients, which increases fear of contagion. Care work is often underpaid and women are generally paid less than men. In addition, more than men, women are expected to make sacrifices for the benefit of others (e.g., children, elderly, or diseased people) whom women are also supposed to care for at home. Consequently, women are at greater risk of being overburdened by domestic tasks (Bahn et al., 2020; López‐Atanes et al., 2020; McLaren et al., 2020).

Qualitative studies, as well as expert commentaries, have discussed aspects that can enhance HCWs' morale. For example, having their sacrifices recognized by patients, government officials, and the general population is a source of motivation, although it cannot be directly controlled. But other aspects are under higher control by HCWs and their leaders, and we can interpret them as strategies to mitigate health problems. These strategies can be classified into two interrelated types.

The first type of strategy provides symbolic recognition and emotional support, but without directly addressing objective working conditions. For example: disseminating messages of work recognition from senior colleagues, managers, and public authorities; creating dialogue channels with supervisors; strengthening social bonds and support among coworkers; training in individual skills for “resilience,” such as breathing and relaxation techniques, and activities to reduce stress and anxiety; and creating psychological support systems (Fawaz & Samaha, 2020; Liu et al., 2020; Shanafelt et al., 2020; Sun et al., 2020). These systems rely on mental health professionals and provide HCWs with channels to externalize and treat their anguish, fears, and anxiety in individual or collective approaches. Support can occur either via videoconference or face‐to‐face meeting in spaces adapted to avoid contagion. Smartphone applications can aid in monitoring sleep, diet, and mood. Action research studies show the design and implementation of psychological support systems for frontline HCWs (Albott et al., 2020; Blake et al., 2020; Cole et al., 2020; Geoffroy et al., 2020).

The second type of strategy improves work organization, organizational support, and objective working conditions. For example, providing adequate PPE, updated protocols, Covid‐19 tests, as well as transportation, housing, and food aid for HCWs; creating physical spaces for workers to rest or relax; reserving the last minutes of the shift for discussions and reflections; and assuring adequate remuneration, workload, and dimensioning of the workforce (Fawaz & Samaha, 2020; Liu et al., 2020; Shanafelt et al., 2020; Sun et al., 2020). By advancing in these concrete issues, leaders of health systems and organizations also show frontline HCWs respect and recognition.

We emphasize that workers' mental health is inseparable from adequate working conditions, which includes providing enough time to recover from fatigue. When working conditions deteriorate and workers feel exhausted, rest becomes a priority in the free time. Consequently, initiatives such as training in stress reduction techniques and implementing psychological support systems become ineffective and subject to low compliance (Chen et al., 2020 ). As noted by Belingheri et al. (2020), long work hours, additional shifts, sleep disorders, and stress can damage the immune system and make workers more vulnerable to illnesses and infections. Adequate sleep is therefore essential to preserve the health and performance of the workforce.

Although healthcare managers may face severe restrictions, thus becoming unable to provide ideal working conditions, their attitude toward subordinates has a major effect on the morale of frontline HCWs. Listening to their demands, creating spaces for discussion, and showing efforts to improve organizational support are examples of attitudes that demonstrate recognition and consideration, thereby positively affecting workers (Shanafelt et al., 2020). Conversely, when HCWs are not given a chance to verbalize their difficulties, omissions and absences tend to occur more frequently (Ornell et al., 2020).

Concerning research gaps, we have identified the following opportunities: (i) investigating the work, challenges, and limitations of healthcare team leaders and managers, whose jobs directly affect the level of organizational support for frontline HCWs; (ii) understanding the obstacles to improve working conditions of HCWs, which may include managerial, union, legal, and governmental issues; and (iii) advancing in qualitative empirical research. Since quantitative epidemiological studies have been predominant, expert commentaries based on scholarly literature and professional experience have helped to mitigate the lack of qualitative research.

Changes in work processes

In this group, the articles focus on providing guidelines or protocols to treat patients who are infected or suspected of being infected with Covid‐19. Research topics include patient treatment and management (Bettinelli et al., 2020; Calvo et al., 2020); use of materials and equipment (Dine et al., 2020); (re)organization of spaces (Ahmed et al., 2020); setting priorities (Davies, 2020; Li, 2020); and workforce management, as HCWs need to be tested and trained in view of the novel situation (Cabas et al., 2020). There are both general and specific recommendations for each type of task or health profession. The instructions are mainly based on medical literature, recommendations from health agencies, and the professional experience of frontline HCWs.

The articles of this group are essentially normative, in the sense of establishing what (ideally) should be done to treat patients and simultaneously protect HCWs. Thus, given the peak of hospitalizations and recurrent resources shortage, it is still to be elucidated how HCWs have been dealing with difficulties in complying with the ideal procedures. This gap is partly filled by articles focused on the protection of HCWs, which will be commented on next.

Protection equipment

The articles classified in this group focus on procedures, PPE, and other artifacts designed to reduce the risk of contagion by Covid‐19. The main topics are: (i) training and protocols for the use of masks and other PPE (Tan et al., 2020; Thomas et al., 2020); (ii) performance comparison of face masks (Bartoszko et al., 2020; Iannone et al., 2020); and (iii) protection strategies against the risk of contagion considering the scarcity of materials. The last topic includes low‐cost techniques, artifacts, and solutions for workforce protection (Chien et al., 2020; Cordier et al., 2020; Ibrahim et al., 2020), as well as procedures, heuristics, or decision‐making algorithms to optimize the use of PPE (Cetintepe & Ilhan, 2020; Forrester et al., 2020; Jones et al., 2020; Kampf et al., 2020). HCWs have thus mobilized their experience, intelligence, and creativity to mitigate the consequences of a shortage of PPE and other materials.

Protection strategies in the context of a shortage of materials have so far mostly referred to frontline HCWs' and their supervisors' responsibility. It is still unclear how hospital and health system managers of middle and top ranks should solve or work around this issue.

Working conditions

The articles classified in this group address different aspects of working conditions, such as availability of PPE (Almaghrabi et al, 2020; Felice et al., 2020), Covid‐19 infection control (Mhango et al., 2020), workload (Belingheri et al., 2020; Zhang et al., 2020), training, supervision (Ballard et al., 2020), financial support and protection for family members (Bayham & Fenichel, 2020), and labor rights (Ghilarducci & Farmand, 2020). The set of articles shows that, amid the pandemic, working conditions have suffered severe restrictions, thereby threatening workers' health.

Although working conditions are essential to fight the pandemic, we note that so far, literature has not clarified how the different levels of management in health organizations and systems can ensure adequate working conditions—or, at least, improve them.

Human resources: Knowledge, attitudes, and practices

Based on self‐reported surveys, the articles in this group evaluate knowledge, attitudes, and practices of HCWs regarding the following issues: general characteristics and forms of transmission of Covid‐19; protocols to treat infected patients; and protocols to protect the workforce, including the correct use of PPE (Asaad et al., 2020; Moro et al., 2020; Saqlain et al., 2020; Zhang et al., 2020).

The articles suggest that the level of knowledge of HCWs varies significantly across and within countries. Also, it tends to be higher among physicians and nurses (Asaad et al., 2020), and among professionals with higher experience or qualifications (Kamate et al., 2020; Olum et al., 2020).

Exposure of HCWs to excessive, contradictory, or unreliable information available in the media and social networks is a common problem, which should encourage healthcare managers to develop training and information strategies. Self‐administered questionnaires assessing workers' knowledge involve relatively low costs and can be part of these strategies (Huynh et al., 2020; Schwerdtl et al., 2020; Tran et al., 2020).

Remote working

Telemedicine health services (THS) have become critical given the restrictions caused by the pandemic. Even under lockdowns, THS enable advices on self‐care and several routine, nonurgent health problems.

THS have the following advantages: (i) reducing personal contact and displacement to healthcare units, thus reducing the risk of contamination; (ii) reducing fear and anxiety among the population; (iii) enabling HCWs in regions that are less affected by Covid‐19 to attend to patients living in severely affected regions, thereby alleviating work overload among HCWs. The last advantage, however, depends on managers of healthcare units and systems cooperating so as to elaborate common frameworks (Chauhan et al., 2020).

According to Chauhan et al. (2020), THS can be provided in the following modalities: real‐time videoconferencing; remote monitoring with instruments operated by patients (e.g., thermometer, blood pressure instrument, pulse oximetry), without HCWs' physical presence; and robotic carts, screens, or medical equipment controlled by HCWs (Celesti et al., 2020; Yang et al., 2020).

Scholarly literature on THS has so far focused on real‐time videoconferencing, probably since the other modalities demand more investment and a higher level of preparedness, which many healthcare systems do not have. However, the other modalities could become more available if governments and healthcare managers invest in THS solutions in the long term.

The few empirical studies on patients' satisfaction with THS via videoconferencing have reported a high level of satisfaction (Green et al., 2020; Watts et al., 2020). HCWs are nevertheless aware of its risks and limitations, and they have been discussing how to make the best use of it (Thompson & Kramer, 2020; Waller et al., 2020). The resulting clinical recommendations shall be used by healthcare managers to provide adequate training and support for HCWs engaged in THS.

Ethics and other topics

The papers addressing ethical issues show that dilemmas play a major role in frontline HCWs' struggle against Covid‐19. These dilemmas represent contradictory, difficult demands under situations of enormous restrictions and uncertainties. Society's expectations and professional ethics push HCWs to expose themselves to considerable risk whenever necessary to treat patients; however, even rich countries have often suffered from scarce resources to handle the pandemic. This may result in HCWs facing traumatic situations in which neither are they able to properly treat patients nor protect themselves and their families. Feelings such as anxiety, guilt, and confusion may arise, consequently impairing mental health (Kalra et al., 2020; Pawlikowski, 2020).

Based on Menon and Padhy's (2020) classification and other papers addressing ethics in healthcare work, three types of dilemmas faced by frontline HCWs can be identified:

• 1. How should I allocate respirators and other resources when they are insufficient to provide all patients adequate treatment?
• 2. How can I balance the duty to treat patients, on the one hand; and the preoccupation with contracting Covid‐19, falling sick, and contaminating my family, on the other hand?
• 3. If I am feeling exhausted or if I have Covid‐19 symptoms, can I talk frankly to my co‐workers and stay home without being discriminated? Or should I keep working so as to avoid discrimination, at the cost of risking my and my co‐workers' health?

Medical literature has traditionally focused on the first dilemma (Kalra et al., 2020), while the papers of our sample actually focus more on the second than on the first dilemma (Culbertson, 2020; Iserson, 2020; McConnell, 2020; Solnica et al., 2020). Only one of the papers explicitly points to the third dilemma (Menon & Padhy, 2020), which may reflect the scarcity of qualitative research on HCWs fighting the pandemic. The second and third dilemmas are directly involved in HCWs' decision between attending or not to work, which is also a matter of workforce safety, wellbeing, and productivity that should concern healthcare managers too.

There are no straightforward, universal answers to the aforementioned dilemmas. Each HCW faces them uniquely since the risks and available symbolic and material resources vary along time and among individuals and organizations. Healthcare team leaders and managers can nevertheless use the existing literature on ethical dilemmas to improve training and encourage open discussions, thus alleviating the emotional burden of HCWs and showing them support. Managerial and political actions that improve working conditions and promote HCWs' health can also provide them more resources to handle ethical dilemmas (Menon & Padhy, 2020; Pawlikowski, 2020).

3.2.2. Education workers and higher education institutions (HEIs)

Academic work was the second most studied professional category. HEIs and academic community, that is, professors, researchers, students, and university staff, had to adapt work due to the pandemic.

Korbel and Stegle's (2020) survey was responded to by 881 participants, including professors, support staff, and trainees from several countries. Among the respondents, 77% affirmed that their institution had been almost totally closed down, with only essential services staff on site; 19% stated a partial closedown, with half or less of the activities being performed; and the others related an almost completely operational institution.

Studies on changes in academic work have raised interrelated issues that also constitute research opportunities. These issues regard:

• 1. Psychological and emotional support . Quarantine has undermined students' performance and made them feel detached from family, fellows, and friends (Meo et al., 2020). Moderate to extreme levels of anxiety, depression, and stress were reported by 50.43% of 2530 academic workers in Spain (Odriozola‐González et al., 2020). Scientists, especially young ones with short‐term contracts, are prone to become preoccupied with their careers (Korbel & Stegler, 2020). Their work as “someone whose job is to think, reflect and critique” may be seen as nonurgent and irrelevant amid the Covid‐19 outbreak (Hage, 2020, p. 1);
• 2. Workload . Educators and scholars need support to deal with the additional burden (Cleland et al., 2020). Educators have performed extra work and extra role tasks, such as providing emotional support and free extra help to students. They have felt constrained to do so, sometimes to the detriment of family time (Fagell, 2020), a problem that particularly affects women (Boncori, 2020; Gao & Sai, 2020; Korbel & Stegle, 2020). Other important issues are the virtual invasion of home space (Boncori, 2020) and the inaccurate expectations of productivity held by co‐workers and supervisors (Ryvasy & Michalak, 2020);
• 3. Resources and infrastructure . Both faculty members and students have had problems on this matter, which includes difficulties with Wi‐Fi connection (Reyes‐Chua et al., 2020), online teaching, software, and technical failures (Pather et al., 2020);
• 4. Skills . Educators lack training on technological tools for teaching and assessment (Reyes‐Chua et al., 2020), new pedagogies, effective communication strategies (Pather et al., 2020), and skills to succeed as a remote worker (Ryvasy & Michalak, 2020);
• 5. Research . Editors and reviewers can discuss how to adapt the peer‐review process given that publishing on topics related to Covid‐19 are strategic, but simultaneously academics have been facing work overload during the pandemic (Eisen et al., 2020).

Faced with so many challenges, HEIs should keep records of transformations in the field of research, training, and education (Cleland et al., 2020).

3.2.3. Other economic sectors

Although studies on workers of other economic sectors are few, they provide valuable contributions not only to understand the impact of Covid‐19 on specific sectors but also on management and organizations in general.

Research on manufacturing firms has revealed effects regarding flexible work arrangement (FWA), job satisfaction, and innovative work behavior. On the one hand, FWA can positively influence work‐life balance, psychological wellbeing, work motivation, and work effectiveness, especially among millennial employees. Work effectiveness, in particular, can benefit from adaptability (Sedaju et al., 2020). On the other hand, the fear of being replaced by digital technologies has increased. Manufacturing employees may be impelled to show more engagement and innovation since they face the threat of job loss amid the Covid‐19 crisis and the rapid advances in digital technologies and artificial intelligence. Younger employees seem to be more comfortable with and more capable of coping with organizational changes caused by the pandemic (Ren et al., 2020). These effects must be considered by managers in light of sociocultural and economic diversity (Sedaju et al., 2020; Tran et al., 2020).

The impact of the pandemic on information technology (IT) is addressed from two perspectives: cybersecurity and HRM. With much more staff working from home than many IT teams have likely ever prepared for, organizations are especially vulnerable, which affects both IT professionals and workers in general. As people lack cyber knowledge, IT professionals are urged to develop new methods of work control, measures, and policies to ensure digital security for teleworkers, who may be required to install security software (Chapman, 2020). This can result in increased pressure, permanent alertness, feeling of being watched, and fear of 24/7 reporting, thereby impairing internal communication, relationships, organizational climate, job satisfaction, and wellbeing (Prasad et al., 2020). In a post‐Covid‐19 world, HRM departments may be reoriented to broaden the recruitment approach and move away from traditional funnels, that is, seeking professionals with different backgrounds and not only graduates of top universities (Chapman, 2020).

In the food industry, specifically in meat and poultry processing facilities, effective prevention and control of Covid‐19 entail challenges in different dimensions: operations (e.g., maintaining physical distancing, including during breaks and when entering or exiting facilities), communication and culture (e.g., dealing with language and cultural barriers), and HRM (e.g., employees incentivized to work despite feeling sick, particularly when there are productivity bonuses) (Dyal et al., 2020). Despite the vital contribution of catering, retail, and other sectors of the food industry to societies, and the fact that many workers of these sectors cannot work remotely, the impact of Covid‐19 on them remains virtually unaddressed in the scientific literature.

In the airline industry, as travel restrictions increase, the most affected employees are the ones responsible for flight operations and handling passengers. Business models have been differently impacted: regional, lean airline companies have received more passengers, while major airlines have contracted routes out. Lean organizations benefit from lower costs and may substitute part of major airline capacity (Sobieralski, 2020).

Lastly, in the apparel industry retailers' shops are being closed with zero turnovers, which leads to ordering cancellation. Due to the relation with the fashion industry, entire seasons may be lost (Sen et al., 2020).

4. DISCUSSION: CONTRIBUTIONS FROM ERGONOMICS AND PDW

In the previous section, the analysis of the sample of articles allowed us to reach our first research objective, that is, to reveal the research gaps and managerial challenges concerning the impact of Covid‐19 on work and workers. To achieve the second objective, namely, helping organizations understand how to adapt work while remaining competitive, we will discuss the results based on concepts of ergonomics and PDW (Figure ​ (Figure4). 4 ). Both disciplines not only focus on workers' activities and challenges but also conceive work, organization, and management inseparably.

Impact on work and managerial challenges from ergonomics and psychodynamics of work (PDW) perspectives

4.1. Adapting work to workers

The pandemic has caused a major impact on work, impelling managers to change work organization and production systems. As advised by ergonomics, this should be done by adapting work to workers and seeking a balance between system performance and human wellbeing (IEA, 2020 ). This concept can be applied to all managerial challenges found in the systematic literature review and serve as a basis for our discussion. Nevertheless, the actual ability of companies to adapt work and promote safety in the specific context of the pandemic, and how this may depend on variables such as company size and type of employment contract, is a matter that deserves further empirical investigation.

4.2. Construction of health and centrality of work

Amid the health risks in the Covid‐19 pandemic scenario, we highlight that work plays a key role in the dynamic construction of health . In contrast to the classic view focused on reducing health risks, the perspectives of ergonomics and PDW argue that work can foster physical and mental health associated with social wellbeing. This relates to another concept of PDW, namely the centrality of work (Dejours & Deranty, 2010 ), according to which work is central to the lives of individuals and the construction of society. These two concepts can assist managers in dealing with the challenge of developing support systems for workers .

4.3. Multifaceted characteristic of health at work

Besides the fear of contamination by Covid‐19, managers should not forget various other aspects affecting workers' health. These aspects may be directly, indirectly, or even not connected to Covid‐19. Ergonomics can help to map them based on different domains of specialization: physical‐environmental, psychosocial‐cognitive, and organizational (Falzon, 2004 ). Regarding the physical‐environmental aspects, the risk of exposure to Covid‐19 should certainly be reduced. This has been studied in scholarly literature, especially in the context of hospital care, and can be associated with the managerial challenge of dealing with resource limitation and supply chain management , given the risk of a shortage of PPE, tests, drugs, and vaccines. However, managers must not neglect other physical and environmental risks, for example, those related to biomechanical issues—including when remote working is implemented. When working at home, uncomfortable equipment and furniture, long work hours, and inappropriate postures can damage workers' health (Davis et al., 2020 ).

Managers should also strive to minimize psychosocial‐cognitive risks. Literature is extensive on this subject, which can be associated with the managerial challenge of promoting psychological wellbeing . It should be reminded that workers under considerable risk of contamination by Covid‐19, for example, the ones in the frontline of manufacturing and service industries, are also vulnerable to emotional and ethical issues, which may generate stress, anxiety, depression, and burnout (Silva & Neto, 2021 ). The impact of the pandemic on people's personal and professional lives can make them feel isolated. Thus, strategies for physical distancing should be created, taking into account workers' mental health and support systems (Bentley et al., 2016 ).

Finally, organizational aspects—which particularly concerns macroergonomics (Brown, 1990 ; Hendrick & Kleiner, 2001 )—must be considered since the pandemic has imposed changes and limitations on production processes and work in organization. Two aspects that managers should particularly consider are job insecurity and work‐life balance. The first is inherent to the economic consequences of the pandemic, which results in managerial challenges linked to economic vulnerabilities , especially in developing countries (Khanna, 2020 ). The second aspect is strongly related to remote working . Other aspects can also be mentioned: increased work rhythm, greater cognitive effort, need for training, and rethinking professional development. Therefore, organizational aspects are not only related to human resources management  but also to the centrality of work to individuals' lives and society.

4.4. Task, activity, and variability

An important theoretical contribution of ergonomics is the distinction between task and activity (Wisner, 1995 ). Task is the work prescribed a priori by the organization, whereas activity is the work effectively carried out by the worker. An accurate view of work situations must take into account the difference between task and activity since tasks themselves are not enough to determine what workers should do. They have to deal with variability and unforeseen events in the inputs and processes of production, which can be intensified due to events that either cannot be or had not been accurately foreseen by managers, such as a pandemic. Among the challenges identified in the systematic literature review, adapting general recommendations for each organization , protective equipment , and strategies for physical distancing indicate that organizations must update procedures. Managers should consider the reality of and variability in activities so that new prescriptions are effective. For example, if the provided PPE greatly hinders the performance of activities, it is likely not to be used by workers; or if the new recommendations are perceived as too bureaucratic, they are likely not to be implemented. Prescriptions are thus more likely to be effective when based on a detailed analysis of work activities, which affords realistic expectations on what workers can actually achieve and endure (Daniellou et al., 2010 ).

4.5. Developing the manager–worker relationship and creating supportive workplace environments

Ergonomics defend that work should first be understood to be adequately transformed (Guérin et al., 2007 ). By developing a close and trustful relationship with workers, managers become more able to understand activities and how to successfully improve work organization. Also, workers should be allowed to be actively involved in (re)designing work, as argued by constructive ergonomics (Arnoud & Falzon, 2015 ). This participatory approach increases the chances of organizational changes to be actually embraced by workers, therefore avoiding waste of resources in solutions eventually rejected by workers. In this sense, we point to the managerial challenge of involving workers from all hierarchical levels .

PDW, in its turn, provides concepts that help to develop  supportive workplace environments . The subjective relationship with work is key in the construction or deterioration of health (Dejours, 2015 , p. 2), but managers' role in this process is often poorly discussed. From the point of view of PDW, work‐related pathogenic suffering typically begins when the relationship between individual and organization is blocked, and when the worker has done all he/she could to deal with difficulties and dissatisfactions, but eventually achieved no success. This means the worker has exploited all personal resources (e.g., knowledge, abilities, creativity, vigor, support from family) and is now unable to meet and vulnerable to the rigid demands of the organization, such as tasks, goals, and deadlines. Hence enabling workers to discuss tasks and organizational choices is essential to preserve workers' health (Dejours, 1992 , p. 52). Nevertheless, it depends on creating a supportive workplace environment, where workers can rely on their colleagues and supervisors to open up about their difficulties without fear of pejorative judgments (Brunoro et al., 2020 ). We stress managers' shared responsibility in this process. Regarding work‐related health issues, simply implementing solutions (e.g., providing external psychological support) without addressing work organization is unlikely to be successful.

Furthermore, we argue that supportive workplace environments contribute to enabling environments from the point of view of ergonomics. Enabling environments mean “debatable” organizations where workers can use their knowledge to adapt its characteristics (e.g., rules, goals, layout, equipment), thus developing both organizational and individual capabilities (Arnoud & Falzon, 2015 ). This can help managers, especially in the pandemic scenario, where many assumptions underlying previous organizational choices do not apply anymore. Managers are, therefore, impelled to collaborate with their subordinates to diagnose a complex, novel situation and reorganize work based on updated assumptions and realistic expectations.

With respect to the service industry, so far, it has not been investigated how to establish sanitary safety rules for clients (e.g., use of masks, physical distancing) and how to deal with clients that do not or refuse to comply with these rules. These issues are challenging, but they are also an opportunity for managers to express support for frontline service workers. According to the principles of ergonomics (Arnoud & Falzon, 2015 ; Guérin et al., 2007 ), the rules for clients should be designed together with frontline workers and consider the specificities of the work situation.

We can observe novel ways in which work is central to but also made invisible by individuals and societies. For example, many occupations officially recognized as “essential work,” such as the ones responsible for cleaning and delivery services, have so far received little scholarly attention. In various countries, these occupations have been subject to a downgrade in labor rights and working conditions, which means governments are failing in properly recognizing their contribution to society. Healthcare work also deserves to be discussed vis‐à‐vis effective labor rights and working conditions, and not only the “heroic” sacrifice societies expect from them. It is also a matter of social injustice that “essential workers” often work under poor working conditions, earn low wages, and cannot refuse unsafe work due to financial restrictions, thus risking their lives and their families. Concerning teleworking, middle and particularly top managers should be aware that, in general, women and workers of lower ranks have fewer chances to keep high productivity levels. Various factors are involved, for example, children or elderly to care for, support from family members, house size, availability and cost of office supplies, the comfort of office furniture, and quality of internet connection. Hence managers should investigate these factors, strive to provide organizational support and be careful in defining reasonable goals, thereby forestalling exhaustion of the workforce.

We add that, due to the vast impact of the pandemic, people may be induced to believe that all should make sacrifices to maintain social functioning, which can particularly affect workers of sectors such as health and education. The expectations on subordinates, colleagues, and even ourselves, are therefore prone to be unrealistic since individuals face different conditions. According to ergonomics, understanding interindividual variability among workers is key to designing sound and suitable work guidelines, processes, and goals (Guérin et al., 2007 ).

Lastly, although the healthcare sector has been predominant in the literature of Covid‐19 effects on work, it provides managers from all sectors important lessons:

• 1. Creating spaces for workers to express their difficulties without fear of retaliation or workplace discrimination is essential to understand what managers can do and how they can tailor solutions considering the specificities of each team and organization. Furthermore, it shows workers support and consideration, thus helping to alleviate their emotional burden and foster trust in the workplace.
• 2. Given the enormous restrictions imposed by the Covid‐19 pandemic and its consequences, managers' capacities are also expected to diminish. Thereby we stress that not only what managers can effectively do counts but also how they relate with their subordinates and communicate them their efforts and limitations in improving organizational support.

5. CONCLUSION

The scholarly literature on the impact of the Covid‐19 pandemic on work has so far focused on frontline HCWs. This unbalanced coverage is not only understandable but also points to many research opportunities. Literature is rapidly advancing and providing healthcare managers valuable ideas to reduce the negative impact of the pandemic on HCWs, for example, improving training, information, and communication strategies; adapting procedures to optimize the use of PPE; investing in solutions that increase the protection of HCWs and their families; and supporting HCWs engaged in telemedicine. Scholars can contribute by making analogous advances in other economic sectors, that is, investigating the specific challenges of each occupation—including those understood as “essential work”—and providing managers recommendations. Even in the health sector, though, it is still not clear how middle and top managers' work is being affected, nor how they can solve or resolve the challenges imposed by the pandemic. Additionally, given the need for physical distancing, researchers of work sciences can benefit from discussing and exploring new methods for field research, thereby becoming more able to investigate the impact of Covid‐19 on the various occupations.

Regarding the limitations of this study, we have not focused on how decisions by public authorities affect work, although this is an important issue to respond to the pandemic and also an opportunity for future research. Also, when selecting the papers of the sample, conference papers were not considered due to the reliability of information and the sample size.

The Covid‐19 pandemic implies numerous managerial challenges. In this article, we raised some concepts from the scientific disciplines of ergonomics and PDW that can assist managers in dealing with or overcoming these challenges. Specifically, we pointed to the construction of health, interindividual diversity and variability, subjective relationship with work, supportive workplace environment, and organizational and individual capabilities. More than before, increasing the flexibility and resilience of organizations through a communicational approach, and involving workers in decision‐making processes, can be critical success factors.

Supporting information

Supporting information.

ACKNOWLEDGMENTS

This study was financed by the Coordination for the Improvement of Higher Education Personnel (CAPES, Brazil)—Grant nb.: 1808446, Finance Code 001. 

Sigahi, T. F. A. C. , Kawasaki, B. C. , Bolis, I. , &  Morioka, S. N. (2021). A systematic review on the impacts of Covid‐19 on work: Contributions and a path forward from the perspectives of ergonomics and psychodynamics of work . Hum. Factors Man . 31 , 375–388. 10.1002/hfm.20889 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

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• Open access
• Published: 16 September 2021

Employment and working conditions of nurses: where and how health inequalities have increased during the COVID-19 pandemic?

• Alba Llop-Gironés   ORCID: orcid.org/0000-0003-0270-3159 1 , 2 , 3 ,
• Ana Vračar 4 ,
• Gisela Llop-Gironés 5 ,
• Joan Benach 1 , 6 , 7 ,
• Livia Angeli-Silva 8 ,
• Lucero Jaimez 9 ,
• Pramila Thapa 10 ,
• Ramesh Bhatta 11 ,
• Santosh Mahindrakar 12 ,
• Sara Bontempo Scavo 13 ,
• Sonia Nar Devi 14 ,
• Susana Barria 15 ,
• Susana Marcos Alonso 16 &
• Mireia Julià 1 , 2 , 3  

Human Resources for Health volume  19 , Article number:  112 ( 2021 ) Cite this article

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Nurses and midwives play a critical role in the provision of care and the optimization of health services resources worldwide, which is particularly relevant during the current COVID-19 pandemic. However, they can only provide quality services if their work environment provides adequate conditions to support them. Today the employment and working conditions of many nurses worldwide are precarious, and the current pandemic has prompted more visibility to the vulnerability to health-damaging factors of nurses’ globally. This desk review explores how employment relations, and employment and working conditions may be negatively affecting the health of nurses in countries such as Brazil, Croatia, India, Ireland, Italy, México, Nepal, Spain, and the United Kingdom.

Nurses’ health is influenced by the broader social, economic, and political system and the redistribution of power relations that creates new policies regarding the labour market and the welfare state. The vulnerability faced by nurses is heightened by gender inequalities, in addition to social class, ethnicity/race (and caste), age and migrant status, that are inequality axes that explain why nurses’ workers, and often their families, are exposed to multiple risks and/or poorer health. Before the COVID-19 pandemic, informalization of nurses’ employment and working conditions were unfair and harmed their health. During COVID-19 pandemic, there is evidence that the employment and working conditions of nurses are associated to poor physical and mental health.

The protection of nurses’ health is paramount. International and national enforceable standards are needed, along with economic and health policies designed to substantially improve employment and working conditions for nurses and work–life balance. More knowledge is needed to understand the pathways and mechanisms on how precariousness might affect nurses’ health and monitor the progress towards nurses’ health equity.

Peer Review reports

Introduction

Nurses and midwives play a critical role in the provision and quality of care and the optimization of health services resources worldwide. This responsibility has turned to be particularly relevant during the current COVID-19 pandemic, where nurses in the public and private sectors are leading COVID-19 care, testing, triage, and management [ 1 ], placing them to a unique position able to deal with vaccination and near-future health challenges. With all, nurses had been one of the most affected collectives by the COVID-19. According to the International Council of Nurses (ICN), millions of nurses have been infected with coronavirus since the start of the pandemic. Cumulative number of reported COVID-19 deaths in nurses in 59 countries was 2262 at the end of 2020 [ 2 ]. However, this number is likely to be underestimated as the actual number of fatalities of health workers is unknown due to the absence of a comprehensive systematic surveillance system. Although great efforts have been made in recent years to build up an international health information system with a key set of indicators focused on achieving an adequate size and skill mix of nursing personnel to attain various population health goals [ 3 ], the last ICN press release reports that standardized and systematic collection of data on infectious and deaths of health workers is not yet happening [ 4 ].

Available data show that prevalence of COVID-19 infections and deaths varied by country and regions. For example, the Americas region accounted for more than 60% of the nurse deaths due to the COVID-19, where Brazil, the USA and Mexico have the highest number of deaths [ 2 ]. Compared to other health workers, professional nurses and nurse aides are disproportionately affected by COVID-19. CDC data, from six states of the US, show that among the total number of SARS-CoV-2 infection, 32.1% were nurse aides and 29.5% were professional nurses, compared to 3.2% of physicians [ 5 ]. Amongst COVID-19-associated hospitalizations in 13 States of the US, professional nurses account for the largest group (35%), followed by nurse aides (15%) compared to physicians (5%) [ 6 ]. These inequalities on COVID-19 infection and deaths by country are due in part to a lack or shortage of personal protective equipment (PPE), where is higher in low-income and middle-income countries (LMICs) [ 7 , 8 ].

Under usual employment and working conditions, health care workers are known to be at risk for depression, stress, anxiety, burnout or insomnia [ 9 ]. COVID-19 pandemic has the potential to significantly impact on mental health of health care workers. A systematic review found a prevalence rate of 23.2% of anxiety, 22.8% of depression and 38.9% of insomnia. Moreover, this systematic review also found gender and occupational differences, where female and nurses had higher rates of affective symptoms [ 10 ].

Nurses and other health care workers can only provide quality services if their work environment provides adequate conditions to support them [ 11 ]. Today, employment and working conditions of many nurses worldwide are precarious [ 12 ], and the current COVID-19 pandemic has prompted more visibility to the vulnerability to health-damaging factors of nurses’ globally. Based on the general framework of employment, work and health of Julià adapted from Benach and Muntaner [ 13 , 14 , 15 ], nurses’ health is influenced by several factors. This conceptual framework shows how labour market and welfare state policies influenced by power relations impact on employment conditions. Thus, labour regulations influence how employment conditions are regulated through the different types of contract. Labour relations are the ones that influence the process of precarious employment conditions. Precarious employment measured through different dimensions is present to a greater or lesser extent in the different employment conditions that, directly or through working conditions or material deprivation, produce an impact on mental health, the self-perceived health and health inequalities. Furthermore, unpaid household and care work also has an influence on health and health inequalities. As for social and family networks, they also have an impact on health, depending on whether they are present or not. Inequality axes like gender, age, social class, ethnicity/race and migrant status are key relational mechanisms of generating inequalities.

The aim of this review is to explore how structural social determinants may be negatively affecting the employment and working conditions, practice, and nurses’ health, also during the COVID-19 pandemic, at the global level.

Methodology

A multidisciplinary team consisting of bedside nurses, activists, union members, and researchers, including nurses’ researchers across nine countries in Asia, Europe and Latin America adopted a collaborative process of critical reflections to guide the understanding of the mechanisms by which nurses’ health is affected, pre-pandemic and during current COVID-19 pandemic.

A desk review was conducted on scientific literature and grey literature, including media, reports, and other relevant resources from various countries including Brazil, Croatia, India, Ireland, Italy, México, Nepal, Spain, and the United Kingdom. We also reported about United States, Australia, and conflict zones such as Palestine, as literature was available. Additional information was sought from Ministries of Health.

Pubmed and google searches were conducted combining the key related terms “nurse”, “employment”, “working conditions”, “health” and “COVID-19” according to the guiding priority areas based on the following topics of the theoretical framework [ 13 , 14 , 15 ]: employment relations in nursing, power hierarchy, and employment and working conditions of nurses. Figure  1 provides a visual description of the adapted theoretical framework of the employment, work and the impact on nurses’ health.

Adapted theoretical framework of the employment, work and the impact on nurses’ health

A total of 77 articles were reviewed, which included 39 research articles, an additional 12 reports, 1 book, 1 thesis, 2 clinical guidance, 2 national official gazette and 20 news articles, as identified by the research team. We based reviews on inputs from the multidisciplinary working group that guided the conceptualization and analysis of the information. Thus, the search was not intended to be exhaustive. We met virtually and discussed by email the emergent findings. Recognizing the importance of the lived experiences, bedside nurses provided a unique contribution to the topic.

Employment and working conditions of nurses

Employment and working conditions before and during the covid-19 pandemic.

Before the COVID-19 pandemic, there has been a marked increase in precarization and/or informalization of nurses’ employment globally that had an impact on working hours and conditions, minimum wage, social protection, and job insecurity. For example, in Mexico during the period 2005–2018 they reported an increase of informalization among the group of nurses analysed in relation to: (a) the percentage of people without a written contract; (b) the percentage of people with incomes lower than two times the minimum wage; (c) the percentage of nurses without social security, and (d) the percentage of nurses without social benefits [ 16 ]. In Catalonia, results of a study show that the highest level of job insecurity occurs among nurse aides and in privately managed nursing homes [ 17 ]. In the growing private sector in India where permanent contracts are rare, nurses were often paid less or just above the minimum wage [ 18 ]. Similar to the case of Australia, where the employment conditions are worse in the private sector which lead to increased mortality in nursing homes [ 19 ]. Also, nurses were already facing structural challenges in many countries as lack of energy and water supply, internet access, enough clean uniforms, appropriate space for breaks, lockers or changing rooms and laundry services, as well as lack of safety, for example during night shifts in isolated areas [ 12 ]. Evidence from countries in South Africa [ 20 ], Kenya, Tanzania and Uganda [ 21 ], Catalonia [ 17 , 22 ], Brazil [ 23 ], Chile [ 24 ], Colombia [ 25 ], Mexico [ 26 , 27 , 28 ], and Thailand [ 29 ] show that employment and working conditions of nurses before this pandemic were already associated to poor physical and mental health, and in some cases leading to fatality outcomes as suicide [ 30 , 31 ]. A particular mention to the nurses working in conflict and war zones. For example, previous to the COVID-19 pandemic, nurses in Palestine reported continuous exposure to traumatic events, and a related feeling of general powerlessness [ 32 ]. As the pandemic spread, these occurrences interlinked with additional problems and continuous blockades, including lack of PPE, guidelines and long working hours [ 33 ].

During COVID-19 pandemic, nurses, as other healthcare workers, have been working longer hours and/or with different shift patterns, and nursing staff has been reassigned from other clinical areas to, for example, ICU [ 34 ], current employment and working conditions of nurses are associated to poor physical and mental in the pandemic context [ 35 , 36 ]. However, differences in employment and working conditions during the pandemic disaggregated by gender, race or the other inequality axes have not yet been studied.

Technical division of nurses’ work

A number of countries have a majority of the nursing workforce composed of nurse aides. This is the case of Brazil [ 37 ], where currently nurse aides account for the biggest number of deaths of COVID-19, more than of professional nurses [ 38 ]. Nursing students, despite traditionally not being considered employees, play a significant role in the health care work during their period of clinical practice and there have been reports of students bullied and breach of working hours agreement, including an enlarged schedule during the night time or weekend hours, as well as a lack of recognition of their work [ 39 , 40 ]. Also, in Denmark there is evidence that immigrant students from Eastern Europe, Iran, Pakistan, Africa or Asia are at significantly higher risk of being bullied in colleges compared to their native counterparts [ 41 ]. In addition, during the pandemic, nursing students of the last year with limited experience in the clinical practice have been sent to the hospitals to work with high-risk patients being underpaid and exposed to big risk-hazards without being qualified to handle such clinical situations [ 42 ]. In Spain, nurses who were in an advanced nursing practice course were reabsorbed as clinical nurses with similar responsibilities but underpaid.

Personal protective equipment

Nurses from different countries reported that the national guidelines and hospital protocols were not well-known among all the nurses working in different settings and sometimes conflicting advice existed, which is in line with current literature [ 35 ]. Nurses reported to work based on their experience and knowledge and perceived confusion about adequate procedures for dressing and undressing with the PPE. Lack of PPE was commonly reported by many health workers globally, also in rural areas and the private health sector [ 43 ]. They had to purchase their own PPE, when available outside the hospital, reuse old PPE and collaborate together to develop alternative tools for protection [ 44 , 45 ]. Furthermore, some units such as maternity wards or primary health care facilities have been considered “low risk settings” despite the possibility of positive cases, which again influenced the accessibility of adequate PPE. A report from the United States shows that primary care physicians are the largest subset of physician deaths [ 46 ], but data on nursing is unavailable. Evidence shows that nurses who do not consider the availability and quality of PPE to be adequate had significantly higher levels of depression, anxiety, and stress [ 35 , 36 , 47 ].

Testing and denial of access to health care

Mass testing of asymptomatic health workers during COVID-19 pandemic has been discussed based on the idea that it might not be necessary in health facilities with protocols for PPE [ 48 , 49 ]. However, one study suggests that weekly screening staff might reduce their contribution to transmission by 25–33% on top of other measures, such as the health workers self-isolation if they develop symptoms [ 50 ]. This is also reinforced by CDC advice to test asymptomatic health workers without known or suspected exposure to SARS-CoV-2 working in nursing homes [ 51 ]. Currently, there are countries that are systematically offering testing to nurses, such as Italy [ 52 ].

There has been less discussion on the determination of payment or insurance coverage of testing or in the case of infection or death of the nurse. For example, in Mexico, a number of nurses have been affected by COVID-19 and they have not had access to testing [ 53 ]. Also, in Nepal most of the private health facilities and hospitals have not insured nurses working in COVID-19 wards, who are at higher risk of being infected with COVID-19 [ 43 , 54 ].

COVID-19 vaccine

Nurses play a key role in the immunization of the population. However, the majority of the countries that have nurses vaccinated are high- or upper-middle-income countries. Frontline workers are considered, globally, a prioritized group but it can be the case that a healthy young person from a high-income country is vaccinated first than a bedside nurse in a low-income country or nurses working in conflict and war zones [ 55 ].

Power hierarchy: inequality axes

Inequality axes such as gender, social class, and ethnicity/race (and caste), in addition to age and migrant status, are key relational mechanisms that explain why nurses’ workers, and often their families, are exposed to multiple risks and/or poorer health [ 13 , 14 ]. This may raise questions as for example who is more exposed during health care related work? Power relations and the social positioning in health systems have traditionally valued medical doctors over nurses, and medical structures over communities [ 56 , 57 ]. This is illustrated by the extraordinary financial compensations provided to healthcare workers exposed during the first wave of the COVID-19 pandemic in some European countries where professional nurses and nurse aides received less, or nothing, compared to their fellow medical doctors. For example, in Catalonia (Spain), compared to medical doctors, professional nurses received 200 euros less, and nurse aides 650 euros less, based on supposed “productivity” criteria [ 58 ]. Another example is the United Kingdom that directly overlooked nurses explicitly saying: “reflecting the vital contributions public sector workers make to our country, these pay rises cover the armed forces, teachers, police officers, the National Crime Agency, prison officers, doctors and dentists, the judiciary, senior civil servants and senior military personnel” [ 59 ]. Also, in India, doctors were given accommodation best-quality hotels near the hospital while nurses stayed in unsanitary dormitories [ 60 ]. Finally, nurses from different countries has reported that the distribution of the PPE has been based on the medical hierarchy rather than the needs of the health workers or the community itself [ 61 ]. This hierarchy has been replicated with the administration of vaccines in countries as UK, Italy and Spain.

Despite nurses being the most trusted health workers in clinical settings, discrimination, stigma and violence against nurses as potential vectors of infection are on the rise during the COVID-19 pandemic, hampering nurses’ physical and mental health [ 34 ]. Health workers in countries like India are being excluded from communities, evicted from their homes and forced to sleep in hospital bathrooms and on floors for fear that they may be carry the coronavirus [ 62 ]. In the city of Rimini in Italy, 70 cars of health workers were damaged overnight outside the hospital [ 63 ]. In Mexico, cases of physical and verbal assaults on health workers, including nurses, have been documented both inside and outside hospital facilities, as well as while making home visits to assess patients, and on their way home [ 64 ].

Nursing workers are predominantly women accounting for 89% of nurses, with variations across world regions; for example, in Africa women represent 76% of the nursing workforce and in South-East Asia 89% [ 12 ]. However, only 25% of health leadership positions globally are held by women or nurses [ 65 ]. Furthermore, although there is no international data on the gender pay gap disaggregated by health workers, there is evidence of a gender pay gap in the health and social work sectors, both in the public and private sector. On average, the gender pay gap amounts to 26% in high-income and 29% in upper-middle-income countries [ 66 ]. In the case of the United States, women nurses earned on average only 91% of what men nurses earned [ 65 ], and we can assume that such a gap exists in other countries as well. The association between the gender pay gap and “family gap” is also significant [ 67 , 68 ]. While for men the salary increases with the number of children, each additional child that women have is associated with a drop in the salary [ 67 ]. Yet, there is a lack of such information based on the study of the nursing conditions.

A predominantly female nursing staff requires a range of work time arrangements, such as extended work shifts, night work, and on-call scheduling. The inappropriate use of these arrangements has been shown to negatively impact the health of nursing personnel [ 69 ]. During COVID-19 pandemic, the burden of nursing workload for women and their “second shift” as key caregivers within their families added additional stress and fear of infecting family or cohabiters [ 35 ].

CDC data from six states of the US suggest that professional nurses, nurse aides, and women are disproportionately affected of COVID-19, despite men being at highest risk of case fatality [ 5 ]. Furthermore, during the first wave of COVID-19 pandemic, there has been a lack of consensus and clear information regarding risks for pregnant women workers exposed to COVID-19 which resulted in hospitalizations and deaths. For example, about 18% of the pregnant women analysed needed hospitalization in 13 states of the United States, 2 (1%) were admitted to the ICU, and 1 (0.5%) required invasive mechanical ventilation [ 6 ], also there are reports of pregnant women deaths [ 70 ].

Ethnicity/race and caste

There are several examples of discrimination as a result of the race, ethnicity and caste. For example, the nursing workforce in countries like the United States is still predominantly White (75%) as a result of privatization of nursing education that creates unequal access to education, and has left many nurses indebted when they finish their studies, putting pressure on them to take available employment regardless its conditions [ 71 ]. Also, colonial legacy and the history of Indian nursing are causes of exploitation and discrimination of Indian women nurses [ 72 ].

During COVID-19 pandemic, studies conducted in the United States show that Black essential workers are at higher risk of infection and death of COVID-19 compared to their White counterparts. It has also been shown that Black workers were nearly three times more likely than White workers to hold support roles in health care, such as nurse aides or orderlies [ 73 ]. Additionally, CDC data from six States of the United States show that American Indian, Asian and Black health workers are at higher risk of case fatality [ 5 ].

Migrant status

Globally, one in eight nurses practises in a country other than the one where they were born or trained [ 34 ]. According to OECD data in 2018, the proportion of migrant nurses accounts for 26% of the nursing workforce in New Zealand, 25% in Switzerland, 18% in Australia or 15% in the United Kingdom [ 74 ]. During this pandemic, international recruiters have increased their direct advertising to try and recruit scarce healthcare staff from low- and lower-middle income countries in Africa, Asia and the Caribbean [ 34 ]. Discrimination and racism at work in terms of lack of job opportunities, poor career progression or a poor learning environment have been identified as the cause of worse health among migrant and minority nurses compared to native-born nurses [ 75 , 76 ].

In some countries in Europe during COVID-19, there are reports of migrant nurses unable to visit relatives in the country of origin because the hospital administration is not allowing paid or unpaid leave. In addition, many nurses who migrated in search of better job opportunities in the UK were held up and were not able to register due to COVID-19 and the lockdown. The Nursing and Midwifery Council enabled temporary registration for migrant nurses who completed competitive skill examinations, but those who had not finished were forced to wait for more than 2–3 months for such registration, which hampered their right to higher wages. In India, the United Nurses Association arranged safe repatriation of nurses stranded in Saudi Arabia.

Countries are failing to evaluate and respond to the impact of COVID-19 on the physical and mental wellbeing of migrant workers [ 77 ] and data on SARS-CoV-2 infection and COVID-19 deaths in migrant nurses is not systematically collected.

Available information from 106 countries indicates that 17% of the nursing workforce are aged 55 years or above [ 12 ]. Regional variations in formally employed workforce are, however, important. For example, in the Eastern Mediterranean Region there are 14 young nurses for every one approaching retirement; in contrast, the Americas this ratio is 1.2:1, and in Europe and Africa it is 1.9:1, indicating a much smaller replacement pool [ 12 ].

Exemptions of COVID work for nurses that are more than 50 years of age were not implemented. Many senior nurses were called to work to fill needed care work and retired nurses are working in the COVID vaccination campaigns [ 78 ]. CDC data from six states of the United States show that professional nurses and nurse aides are disproportionately affected and the group of age over 55 years has a significant probability of case fatality [ 5 ].

Employment relations in nursing

The macro-structural framework encompasses the broader social, economic, and political system that exerts significant power over the distribution of resources in a society, shedding light on the complex health and health care politics, and how the redistribution of power relations creates new policies regarding the labour market and the welfare state, namely labour standards, occupational health and safety regulations, and union protections, among many other things [ 13 , 14 , 79 ].

Unions, civil society, and collective bargaining

Nursing professional associations, educational institutions, nursing regulatory bodies and unions, nursing student and youth groups, grassroots groups, and global campaigns such as “Nursing Now” are valuable contributors to strengthening the role of nursing in healthcare teams to achieve better employment and working conditions for nurses [ 12 ].

Unionization in the health sector varies between regions, welfare state regimes and health workers groups, but regions have a similar trend of higher unionization in the public sector compared to the private one. For example, in Europe, the coverage of collective bargaining is notably higher in the public compared to the private sector. Collective agreement coverage in the private sector is considerably low and is even lower for nurses, for example, in the case of Poland, the coverage is only 5% [ 80 ].

Furthermore, while nursing students were employed as actual workers during the COVID-19 crisis, they were not always covered by the existing labour laws and the coverage of collective bargaining in this sector of workers is unknown. For example, a press release from the Irish Nurses’ and Midwives’ Organisation (INMO) points out that students “do not have the protections provided to employee” [ 42 ]. In Mexico, students have claimed that they are not given adequate PPE and hospitals told them that if they leave work, their scholarship will be withdrawn [ 81 ]. However, in England, the unions reached an agreement with the Nursing and Midwifery Council (NMC) and chief nursing officers across the UK that enables more experienced students to work in the NHS, receive remuneration and that this work counts for their learning [ 82 ]. Less has been explored about the role of universities in allowing, enabling and even possibly encouraging their students to enter high-risk health environments [ 83 ].

The International Labour Organization (ILO) Nursing Personnel Convention, 1977 (No. 149) and the accompanying Recommendation (No. 157) set standards for fair employment conditions for nursing personnel. Yet, to date only 41 countries have ratified the Convention. Also, just 20 countries out of 194 Member States of the WHO have reported measures in place to prevent attacks on health workers [ 12 ].

During COVID-19, countries’ general policies do not address nursing work and needs. For example, the current COVID-19 guidance from Public Health England states that a fluid-resistant surgical face mask is sufficient for non-aerosol-generating procedures [ 84 ]. The administration of specific therapies, like Entonox, is not classified as an aerosol-generating procedure; however, a midwife can spend up to 11 hours in an unventilated room with an asymptomatic woman wearing Entonox with no protection other than a surgical mask. Inadequate PPE has been shown to be a source of infection among healthcare workers [ 8 ].

In addition, the declaration of COVID-19 as an occupational disease has been uneven and several countries have not yet developed this policy [ 85 ].

Government, economy, and political priorities

There is evidence of numerous links between the characteristics of welfare state regimes and the regulation of nurse and nursing professionalization, suggesting that the political context has to be acknowledged and addressed to significantly influence nursing employment and working conditions and health policy [ 86 , 87 ]. In addition, the presence of a Government Chief Nursing Officer (GCNO) position and the existence of a nursing leadership programme to effectively take action in government actions, are associated with a stronger regulation of employment and working conditions for nurses and regulation of nursing education [ 12 ]. However, not all countries have a GCNO, and the rhetoric of the dominant groups (i.e. medical doctors) has traditionally been overrepresented in the decision-making compared to nursing [ 88 ]. It is illustrated again with the COVID taskforce of many countries where the involvement of nurses has been negligible or null in coordinating and supervising the governments’ efforts to monitor, prevent, contain, and mitigate the spread of COVID-19. This is for example the case of India [ 89 ].

Regarding the economic situation, the 2008 economic crisis led to neoliberal austerity measures imposed in many countries that significantly curtail government spending. One of the measures implemented set caps on employment in the public sector which had a significant impact in the precarization of nurses [ 90 ]. For example, in Croatia it resulted in overburdening employed nurses; the inability of newly graduated professional nurses to access employment and, therefore, an increase in migration and a deepening of the serious shortage of nursing personnel [ 91 , 92 ]. Other effects of the economy in the current nursing workforce can be found in Mexico, where prioritization in hiring nurses’ aides instead of professional nurses started as a response to the economic development plans of the 1970s that resulted in policies set by Mexico state [ 93 ]. Several countries in South Asia also followed a similar trajectory [ 94 ]. In addition to the direct effect of the austerity measures, a majority of nurses women were also severely affected by shrinking social protection floors with an impact on childcare and elderly care.

The global dynamics in the economy also plays a role, more visible during the pandemic. For example, the country’s purchasing capacity, the availability of PPE or vaccine production capacities, and the international dispute over scarce health workers.

Discussion and limitations

Nurses’ work is essential in the health system as it has been proved once again during the COVID-19 pandemic. Yet, the pandemic has also exposed historic vulnerabilities faced by many nurses’ workers worldwide which resulted in an unacceptable number of infections and deaths among nurses. The neoliberal austerity measures promote precarization and informalization of nursing work and worsened the vulnerability to health-damaging factors, with many countries still to ratify the ILO Nursing Personnel Convention, 1977 (No. 149) on fair employment conditions. However, the current body of evidence lacks a detailed understanding of the pathways and mechanisms on how precariousness might affect nurses’ health. This might be linked to the current limited capacity of health information systems, and the inability to collect, analyse and monitor precarious employment and the impact in terms of health, wellbeing, and equity.

Collective bargaining through participation in unions and networks has proven to be effective in demanding for fairer employment and working conditions, but such collective organizing and legal rights are still insufficient in many countries. In line with this, COVID-19 pandemic has sparked new solidarity actions by nurses to bring more attention to nurses’ concerns, with calls for post-pandemic international and nationally enforceable standards. Some examples of successful actions to increase the number of nurse-centred and nurse-safe spaces to raise concerns and thus improve nursing working conditions during COVID crisis are reported from countries such as Brazil [ 95 ], India [ 96 , 97 ], or Ireland [ 98 ].

The adapted theoretical framework of employment, work and health provides general guidance and helps in understanding the complex causal relations of employment, work and nurses’ health to guide policies and interventions to achieve greater equity. However, it needs to be tailored to the specific historical processes of each country, region or area, and social dynamics of different labour markets. An example is the wage hierarchies and the regulation of nurse and nursing professionalization [ 99 ]. In addition, this conceptual framework must also be considered with a dynamic perspective of the life cycle.

This study acknowledges that the search strategy used for the identification of studies might lead to exclusion of few relevant studies, although the searches performed have been extensive and it has been complemented with the lived experiences of bedside nurses from countries across Asia, Europe, and Latin America. Also, the study was done entirely virtually, and the team was not able to retrieve information from physical archives.

Box 1 describes the main recommendations based on the findings of the study. General recommendations combining policies at different entry points (power relations, employment, working conditions and ill-health workers) need to be specified and contextualized for each territory, condition, and population. Also, international institutions, governments and political parties, unions, and civil society associations favouring fair employment relations are key actors in implementing effective policies leading to the reduction of employment-related health inequalities.

Box 1. Recommendations

Changes in power relations in nursing which can occur between the main political and economic actors in a society:

Public health policies embedded in broader social and economic development planning and public funding should be developed;

Structural drivers of inequality that push most vulnerable nurses, namely migrant, ethnically diverse, younger and older women, into more precarious and exploitative work should be recognized and act upon by them;

Public financing to support gender equity and the needs of nurses' workers should be directed to increase access to the social protection mechanisms adequately funded and fully operational, notably, kindergartens, homes for the elderly, public transport and public housing;

Further investment in public health systems should include the lift of existing caps on employment in the public sector, prioritization of standard employment of nurses in the public health systems and ensure nurses are paid adequately;

National GCNO and nursing leadership programmes should be developed to promote stronger regulation of nursing education and employment and working conditions for nurses;

The right of nurses to organize and join trade unions should be protected and workplace democracy should be recognized.

Modification of employment and working conditions to reduce vulnerability to health-damaging factors:

Countries should ratify the ILO Nursing Personnel Convention, 1977 (No. 149) and act accordingly;

Nursing education should be accessible, free-of-charge and of good quality;

International mechanisms should be in place to regulate nurses’ migration, such as the WHO Global Code of Practice on the International Recruitment of Health Personnel;

Migration policies that are not discriminatory or punitive and ensure that nurses can access public services adequately should be put in place;

Interventions to reduce the unequal consequences of ill-health and wellbeing:

Universal access to health care including occupational health in primary health care should be provided to nurses, including those informalized;

COVID-19 should be declared as an occupational disease;

National capacity of health information systems and the international interlinkages should be strengthened to collect, analyse and monitor precarious employment and the impact in terms of nurses’ health, wellbeing, and equity.

Nurses’ health is negatively affected by their employment and working conditions which in turn are determined by the power hierarchy and nursing employment relations. Current situation aggravated by the COVID-19 pandemic requires of international and national enforceable standards, along with economic and health policies designed to substantially improve employment and working conditions for nurses and work–life balance, reducing the burden of nurses’ “second shift” within their families. Future research should analyse the pathways and mechanisms on how precariousness might affect nurses’ health and monitor the progress (or not) towards nurses’ health equity over time and evaluate the effects of different interventions between and within countries.

Availability of data and materials

Not applicable.

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Llop-Gironés, A., Vračar, A., Llop-Gironés, G. et al. Employment and working conditions of nurses: where and how health inequalities have increased during the COVID-19 pandemic?. Hum Resour Health 19 , 112 (2021). https://doi.org/10.1186/s12960-021-00651-7

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COVID-19 and the labour market: What are the working conditions in critical jobs?

• Matthias Dütsch   ORCID: orcid.org/0000-0003-0936-2422 1  

Journal for Labour Market Research volume  56 , Article number:  10 ( 2022 ) Cite this article

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The COVID-19 pandemic has focused public attention on occupational groups that ensure the maintenance of critical infrastructure, provision of medical care and supply of essential goods. This paper examines the working conditions in critical jobs based on representative data from the German BAuA Working Time Survey 2019. Our analyses reveal that essential workers are more likely to perform unskilled or semiskilled activities and work in cleaning, transport and logistics, health care occupations as well as IT and natural science services. Regarding the working conditions, essential workers are paid comparatively less and are more physically proximate to others at work than nonessential workers. They more often work atypical hours, such as day and night shifts and on weekends, and have less autonomy in their working time. Additionally, critical jobs are characterised by muscular and skeletal strain due to working positions and carrying heavy loads significantly more often. Thus, our findings strongly suggest that work-related risks accumulate in critical jobs.

1 Introduction

The COVID-19 pandemic has dramatically affected individuals’ social and economic lives. Many countries have put in place numerous requirements such as mask mandates and distancing measures and have communicated recommendations for avoiding social contact to protect against infection and contain the virus. In the implementation of these containment measures, the so-called critical economic sectors and critical occupations have become the focus of political and public attention. Government institutions worldwide drew up lists of critical sectors and occupations that are very similar in their composition; workers in these sectors ensure, among other things, the maintenance of systemically relevant infrastructure and the provision of medical care and nursing services and the supply of essential goods (see, e.g., CISA ( 2020 ) for the US, CPNI ( 2021 ) for the UK, and BMI ( 2009 ) for Germany). Unlike other employees who were asked to isolate themselves, work from home, and reduce their social contact at work, essential employees were provided with support measures, such as emergency child care, so that they could continue to perform their jobs.

Examining wages and physical proximity in critical occupations or industries, recent empirical research has indicated that the working conditions in critical jobs are less favourable than those in other jobs and have become even more hazardous during the pandemic. However, referring to theoretical approaches to segmented labour markets (Hendry 2003 ; Osterman 2011 ; Kaufman 2013 ) and research investigating the quality of work (Kalleberg 2011 ; Howell and Kalleberg 2019 ), we argue that it is necessary to investigate a broader range of working conditions since favourable and unfavourable working conditions are often found in a cumulative manner (ibid.). Beyond wages and physical proximity, working time patterns and physical working conditions are two additional crucial considerations. The former are important because working time arrangements influence everyday life (ILO 2018 ) and the organisation of work and family life (Howell and Kalleberg 2019 ). Both became even more significant when the measures to contain the COVID-19 pandemic were in effect since parents, particularly women, had to engage in child care and home schooling to a much greater extent than before. Unfavourable working hours also adversely affect individuals’ health. Furthermore, a wide range of studies have found physical working conditions to be important for individuals’ working lives. Physically demanding labour negatively influences health outcomes and leads to health inequalities and health-related job loss.

Against this backdrop, this paper raises the following research question: What are the working conditions in critical jobs? The study aims to perform a comprehensive analysis of working conditions in critical jobs and contributes to recent research in the following ways. First, we conceptually frame the public and academic discussion about working conditions in critical jobs by arguing that this debate can be linked to theoretical approaches to segmented labour markets. Second, we describe the sociodemographic characteristics of essential workers and structural determinants of critical jobs to enable policy decisions that protect and meet the needs of these workers. Third, we extend recent research on critical jobs by following Kalleberg’s ( 2011 , p. 5) note that working conditions comprise multidimensional bundles of rewards and burdens. Therefore, we analyse wages, a classical dimension of inequality, and physical proximity to others at work, which we consider a new and emerging stressor due to the COVID-19 pandemic, as well as working time patterns and physical working conditions. Understanding which population strata are the most affected and gaining deeper insight into the working conditions in critical jobs is crucial for not only the persons concerned but also policymakers and stakeholders because research has examined the longer-term effects of past crises on labour market outcomes (Killewald and Zhuo 2019 ). Furthermore, employment-related exposure to SARS-CoV-2 endangers not only workers but also their household members (Selden and Berdahl 2020 ).

The empirical analyses are based on the German Federal Institute for Occupational Safety and Health (BAuA, for its German acronym) Working Time Survey 2019, conducted shortly before the beginning of the COVID-19 pandemic and therefore unaffected by it. The Working Time Survey is a representative study that includes detailed information on approximately 9,500 individuals from all industries. It is a unique dataset since it contains individual-level information on wages, physical proximity to others, working time patterns and physical working conditions, as well as the sociodemographic, job-related and structural characteristics of workers and their jobs. With reference to this dataset, employees' jobs were categorised as critical or noncritical based on the classification of systemically relevant supply and care occupations compiled by Burstedde et al. ( 2020 ) during the coronavirus pandemic in 2020. The list is based on the “List of Critical Infrastructures” (KRITIS) developed jointly by German federal states and the federal government in 2009; additionally, the classification of systemically relevant supply and care occupations includes occupations not yet covered by the KRITIS list but of particular relevance in the COVID-19 pandemic. This empirical approach allows us to examine the specific occupational strains that already existed before the COVID-19 pandemic in occupations that became very important during the pandemic. To our knowledge, there are no alternative and longitudinal data to draw representative conclusions about changes in working conditions due to the COVID-19 pandemic. The empirical investigation is conducted in three steps. First, we present a descriptive analysis of the data. Second, we perform binary logistic regressions to determine the likelihood of working in a critical job and, thus, identify the groups of employees concerned. Third, in various regression estimations, we investigate the relationships between critical jobs and working conditions to assess possible accumulation of risks. In doing so, we pursue an explorative approach and provide correlations since we cannot determine causal effects due to the cross-sectional data structure.

The paper is structured as follows. Section  2 describes the current state of research. Section  3 provides a theoretical rationale for the differences in working conditions between critical and noncritical jobs, while Sect.  4 presents the data and the methodological approach. Section  5 reports the empirical results, and Sect.  6 concludes.

2 State of the research

Since the beginning of the pandemic, the literature on the groups of workers affected by the pandemic, as defined by their sociodemographic characteristics, and on the consequences of the COVID-19 emergency for individuals and households has been growing rapidly. However, to our knowledge, only a few research papers have focused on systemically relevant occupations.

Blau et al. ( 2020 ) studied the US labour market and drew on the federal guidelines of the Department of Homeland Security (DHS) and the Cybersecurity and Infrastructure Security Agency (CISA) to identify 194 out of 287 total NAICS industry categories as essential. Additionally, the study identified frontline workers as a subcategory of essential workers: those in occupational groups where a third of workers or fewer can feasibly work from home. They mapped both constructs to microdata from the 2017 and 2018 American Community Survey (ACS). Their descriptive comparison of the gender, race, educational degrees and hourly wages of essential and frontline workers revealed that the demographic and labour market characteristics of the broader group of essential workers tend to mirror their averages for all workers. In contrast, the narrower group of frontline workers is, on average, less educated, earns lower wages and is composed of more men, more individuals from disadvantaged minorities (especially groups of Hispanic ethnicity), and more immigrants. Kane and Tomer ( 2021 ) drew on the 4-digit NAICS industries related to the list of essential critical infrastructure workers and on employment data for each industry from the Bureau of Labor Statistics and defined a subgroup of frontline workers. Their descriptive results indicated that frontline workers earn lower wages and are more frequently required to be physically present in their workplace. Frontline workers also tend to be less educated than other essential workers and the wider US workforce. Essential workers are more often men working in construction, manufacturing, or skilled trades, while female employees in this group are much more concentrated in other essential occupations, such as health care, education, and service activities. Employing household data from the 2018 ACS, which is a random sample of US households, and the DHS list of essential critical infrastructure workers, McCormack et al. ( 2020 ) descriptively estimated that 25 percent of essential workers’ households are low income.

Looking at the German labour market, Koebe et al. ( 2020 ) investigated the social prestige and average wages associated with critical occupations. They used the German Socio-Economic Panel (GSOEP), a representative household survey, and classified “first-hour” and “second-hour” critical occupations based on the list issued by the federal state of Berlin. The list of first-hour critical occupations was published in Berlin on 17 March 2020 and was expanded approximately one month later to include the list of second-hour critical occupations. Footnote 1 The data were operationalised at the 3-digit occupation classification level. By performing descriptive analyses, Koebe et al. ( 2020 ) found that essential employees are more likely to be women, to have below-average social prestige and to report below-average wages. These findings apply especially to first-hour critical occupations. Lübker and Zucco ( 2020 ) relied on German linked employer–employee data in their study and analysed employees in critical economic sectors. Applying logistic regressions, the authors revealed that women are more likely to work in critical infrastructure than men. This is also true for part-time workers and employees with technical jobs. In contrast, individuals without a university degree are slightly less likely to work in a critical sector. An assessment of the wages of full-time employees did not indicate systematic differences between critical and noncritical sectors.

The above review of literature on critical labour during the COVID-19 pandemic shows that many of the research papers have provided only descriptive evidence. The findings, whether for the US or for the German labour market, do not indicate clear patterns regarding the sociodemographics of essential employees. However, essential employees seem to earn comparatively low wages in poorly valued jobs and often perform work that requires greater physical proximity to others than nonessential work.

3 Social inequalities, working conditions, and the COVID-19 pandemic

A theoretical rationale for the differences in working conditions between critical and noncritical jobs is lacking. Against the backdrop of recent studies that have identified apparently coinciding risks in critical jobs, we draw on newer theoretical approaches to human resource management that explain labour market segmentation (Hendry 2003 ; Osterman 2011 ; Kaufman 2013 ). These approaches assume imperfect labour markets and incomplete labour contracts. They emphasise that segmentation, and thus inequalities in the labour market, depend on employees’ and employers’ bargaining power and on the social and structural conditions that frame social actions within the employment system (ibid.).

Since employment relations are determined by the relative power of employers and employees to control tasks, negotiate the conditions of employment, and terminate employment, various aspects of job quality covary. If employers are interested in binding employees to the company for a longer period, they can achieve this through offering more secure and more highly paid jobs, better working conditions and further training opportunities. This creates closed positions in primary segments of the employment system (Hendry 2003 ; Osterman 2011 ; Kaufman 2013 ). In contrast, in more open and, therefore, secondary segments of the employment system, the problem of worker availability is quantitative only and is thus limited to the number of employees in external labour markets. Employees in open employment systems have little power of action in the labour market due to the competitive situation in their occupational field and the lack of representation of their interests. Therefore, this segment of the employment system is characterised by comparatively low wages and unfavourable noneconomic working conditions (ibid.). In fact, scholars could examine several individual, job-related and structural factors (such as gender, age, type of work, existence of work councils, firm size or economic sector) that are strongly associated with individuals’ positions in the primary or secondary labour market segments (Hudson 2007 ; Lucifora and Salverda 2009 ; Howell and Kalleberg 2019 ). Because working conditions are composed of multidimensional bundles of rewards and burdens (Muñoz de Bustillo et al. 2011 ; Kalleberg 2011 ), we consider four crucial components of working conditions in what follows.

First, the core dimension of job quality is certainly wages; wages are also regarded as the most straightforward attribute to measure (Muñoz de Bustillo et al. 2011 ; Howell and Kalleberg 2019 ). Wage inequality has been shown to be substantial and to have risen in many countries (Autor et al. 2008 ; Bol and Weeden 2015 ). Increased inequality across occupations and the associated heterogeneities across workplaces and firms (Card et al. 2013 ; Biewen et al. 2017 ) point to increased segmentation in the labour market. In terms of working conditions, sustained receipt of low wages is a serious issue because they have been shown to negatively influence, amongst other outcomes, individuals’ work satisfaction (Diaz-Serrano and Cabral 2005 ) and health (Kim and Leigh 2010 ; Leigh and Du 2012 ).

Second, as a result of the COVID-19 pandemic, epidemiological risk at work, considered to be a crucial component of working conditions, is not evenly distributed across workplaces and employees (Avdiu and Nayyar 2020 ; Basso et al. 2020 ; Dingel and Neiman 2020 ). Workers who are more highly exposed to aerosols due to a high degree of social interaction at work with customers, clients, and persons in need of care report deteriorated physical and mental health outcomes and face a greater risk of SARS-CoV-2 infection (Mhango et al. 2020 ; Sanghera et al. 2020 ). In contrast, in the case of home office work, work-related face-to-face interactions can be avoided, which reduces exposure to aerosols and therefore the risk of infection (Dingel and Neiman 2020 ).

Third, a further important aspect of working conditions is working time, as the ILO recently emphasised: “Working time, perhaps second only to wages, is the working condition that has the most direct impact on the day-to-day lives of workers” (ILO 2018 , p 2). This dimension is especially relevant to the organisation of work and family life (Howell and Kalleberg 2019 ). Working time arrangements became even more significant when the measures to contain the COVID-19 pandemic were in effect since parents, particularly women, had to engage in child care and home schooling to a much greater extent than before (Alon et al. 2021 ). Furthermore, working time is crucial to employees’ health. Long working hours, including overtime hours, are negatively correlated with physical and psychological health (Bannai and Tamakoshi 2014 ; Kivimäki et al. 2015 ) and are positively correlated with the risk of workplace accidents (Dembe et al. 2005 ; Fischer et al. 2017 ). Regarding atypical working hours, studies have found negative health effects when work must be performed during socially valuable times—on Sundays, for example (Wirtz et al. 2011 )—and particularly during night shifts (Costa 2003 ). Research has also provided evidence that a lack of job control over working hours, such as requirements to be on call or expectations to be accessible at all times, limits workers’ individual autonomy and places demands on employees, constituting stressors that negatively affect health (Väänänen et al. 2008 ; Slany et al. 2014 ). During the COVID-19 pandemic, the greatly increased work intensity was reported as a risk factor for the mental health of medical and nursing staff (Godderis et al. 2020 ; Sanghera et al. 2020 ).

Fourth, physical working conditions are another important aspect of job quality (Muñoz de Bustillo et al. 2011 ). Research has indicated that poor physical working conditions cause severe health problems (Laaksonen et al. 2010 ; Holtermann et al. 2011 ) and health inequalities (Kaikkonen and Rahkonen 2009 ) and lead to health-related job loss (Sewdas et al. 2019 ). Work that primarily requires the use of the musculoskeletal system to accomplish the corresponding tasks is described as physically demanding (de Kok et al. 2019 ). Such jobs include handling manual loads (such as lifting loads), working in forced postures (such as standing, sitting, or bending the torso), working with increased exertion, and completing highly repetitive manual tasks. Numerous systematic reviews have demonstrated the link between physical strain at work and musculoskeletal disorders, which are very common health problems (Holtermann et al. 2011 ). The prevalence of musculoskeletal disorders is associated with high levels of anxiety, sleeping problems and overall fatigue among workers; such disorders are also related to workers’ mental well-being (de Kok et al. 2019 ). Furthermore, physical stress causes, among other problems, cardiovascular diseases (Holtermann et al. 2011 ).

Against this backdrop, we focus on wages, physical proximity to others at work, working time patterns and physical working conditions to assess work-related risks in jobs crucial for the maintenance of social life during the pandemic. In the following section, we first describe the data, our operationalisation, and our method before presenting our empirical findings.

4 Data and methodological approach

Our analyses are based on data from the BAuA Working Time Survey 2019, a nationally representative study of the German working population. The survey was designed and commissioned by the BAuA (Wöhrmann et al. 2021 ). Data from 9,382 individuals were collected in computer-assisted telephone interviews between May 2019 and January 2020—thus, before the COVID-19 pandemic hit Germany. This feature of the data is very important, as it ensures that respondents’ answers about their working conditions were unaffected by the COVID-19 pandemic; thus, unbiased estimates can be assumed. To be eligible to participate, individuals had to be 15 years of age or older and in paid employment for at least 10 h per week at the time of the interview. Employees who had interrupted their employment for longer than three months—for instance, because of maternity leave or periods of sickness—or who were engaged in vocational training or in military, civilian, or voluntary service were excluded. To compensate for survey-related selectivity and to ensure the representativeness of the data, the BAuA Working Time Survey provides weights to match the basic figures from the 2018 Microcensus of the Federal Statistical Office (Häring et al. 2020 ). The advantage of the Working Time Survey is that for the first time, all relevant information on monthly wages, hours worked, physical proximity to others at work, working time patterns and physical working conditions is available within a single dataset; it additionally enables a variety of sociodemographic and structural factors to be included and controlled for. The latter is particularly necessary because the cross-sectional data do not allow us to directly control for the possible selection of certain employees into certain (stressful) occupations. The inclusion of a rich set of covariates in our estimations should control for such selection effects to the greatest possible extent.

Based on the prepandemic data of the BAuA Working Time Survey 2019, to indicate whether an individual works in a critical job, we computed a dummy variable based on the classification of systemically relevant supply and care occupations compiled by Burstedde et al. ( 2020 ) during the coronavirus pandemic in 2020. This classification was developed in several steps. First, critical sectors were identified in the German Classification of Economic Activities (WZ 2008 ) based on the KRITIS list, which was developed jointly by German federal states and the federal government in 2009 (BMI 2009 ). In some cases, Burstedde et al. ( 2020 ) added sectors not (yet) included in the original KRITIS list but that became significant during the pandemic. Second, using data on employees subject to social insurance contributions by occupation and sector from the Federal Employment Agency (BA), Burstedde et al. ( 2020 ) identified occupations operating mainly in these sectors. For this purpose, they used the 1,286 occupational types from the 2010 German classification of occupations (KldB 2010 ). Footnote 2 In most cases, this procedure led to a clear assignment of occupations to critical sectors. However, several occupations had to be examined individually and independently of the sector. To this end, Burstedde et al. ( 2020 ) relied on very detailed descriptions of 28,000 occupational titles (BA 2020a ) and the BERUFENET database (BA 2020b ) and assessed the extent to which the qualifications needed and tasks performed in an occupation were necessary for the production of supply-relevant goods and services or for public safety. Footnote 3

The advantage of this fine-tuned identification of critical occupations based on the 1,286 occupational types is that the KRITIS list could be adapted as objectively as possible to the context of the COVID-19 pandemic. For example, trade was classified as relevant across the board in the original KRITIS list. However, under the COVID-19 pandemic, the sale of jewellery and watches and the music trade were by no means essential for critical infrastructures. In the food manufacturing sector, for example, occupations that produce alcoholic beverages were deemed not essential. In addition, some essential sectors such as waste disposal and funeral services were not (yet) enumerated on the federal government's KRITIS list but were explicitly listed in some federal state pandemic lists. This also applied to occupations in plastics and rubber manufacturing, which were needed during the pandemic for production of respirators and food packaging. Overall, this categorisation led to the delineation of 503 of the 1,286 occupational types as critical occupations. The list of critical occupations can be found in Burstedde et al. ( 2020 : 27ff.) and in the appendix (Additional file 1 : Appendix Table A1). Note, in general, that this occupational classification places special emphasis on the consideration of value chains; this implies that a larger number of occupations were defined as critical than under the narrower definitions of frontline work that have been the focus of public debates in the past (ibid.: 5).

Regarding the outcome variables, the Working Time Survey data allow us to calculate gross hourly wages based on gross monthly wages and weekly working hours. We obtained our figure for gross hourly wages by dividing gross monthly wages by weekly working time, which was multiplied by 4.33. Footnote 4 Individuals who refused to answer the questions on wages and hours worked were dropped. These restrictions left us with a sample of 7,268 cases. We assessed the extent of physical proximity to others at work based on three questions in the Working Time Survey: “How often do you have direct contact at work with people or patients in need of care or assistance?”, “How often do you have direct contact at work with guests, customers or clients?” and “How often do you have direct contact at work with other people not employed by your employer?” Respondents could indicate whether such contact occurred often, sometimes, rarely or never. We created a dummy variable coded with the value 1 to indicate frequent physical proximity when at least one of the three questions above was answered with “often”. In all other cases, the value 0 was assigned, reflecting a work situation in which the employee is sometimes, seldom, or never in physical proximity to others at work. In recent research on physical proximity to others, home office work has been considered the exact opposite of proximity (Avdiu and Nayyar 2020 ; Dingel and Neiman 2020 ). Thus, we also included a home office indicator. Working time patterns are differentiated through measures of the duration of work, atypical work hours (weekly overtime, shift work, and weekend work) and working time autonomy (regularly being on call or standby, making one’s own decisions about breaks, being expected to be accessible in private life, and having the possibility to separate work and private life). Physical working conditions are measured by indicators for muscular and skeletal strain (working in a standing position; working in a sitting position; kneeling, bending, or engaging in overhead work; lifting and carrying heavy loads) and for strain from the working environment (noise; bright, poor, or faint light; cold, heat, wetness, dampness, or draughts; the inability to influence one’s work tasks).

In the first step, we assessed the determinants of working in a critical job with the following statistical model:

where \(cjob\) is the dependent dummy variable (0 = noncritical job; 1 = critical job) following a binary logistic distribution \(\left(P\left(y=1\right)=\frac{1}{1+{e}^{z}}\right)\) . α is the regression constant, and β is the coefficient of the explanatory factors. The latter are added sequentially in three steps. Model 1 contains only sociodemographic (gender, age, place of residence, highest professional degree) and household (marital status, children in household) characteristics, model 2 adds job-related factors (tenure, form of employment, type of contract, job complexity, additional jobs), and model 3 includes structural determinants (size of company, work council) as well as occupational information (14 occupational segments). \(\upvarepsilon\) denotes the error term.

In a second step, we investigated the correlation between employment in a critical job and working conditions. The formal statistical equation of the corresponding estimations is

where z denotes the dependent variable. α is the regression constant, and β is the coefficient of interest indicating the correlation with employment in a critical job. \(\upgamma\) reflects the influence of the other covariates, and \(\upvarepsilon\) is the error term. Hourly wages are logarithmised and estimated using a linear Mincerian regression. The two indicators of physical proximity are binary coded and follow a binary logistic distribution \(\left(P\left(y=1\right)=\frac{1}{1+{e}^{z}}\right)\) . Weekly overtime (in hours) is subject to a linear regression, while the variables on atypical working hours and weekend work adhere to a multinomial logistic function \(\left(\mathrm{P}\left(y=J\right)=\frac{1}{1+\sum_{j=1}^{J-1}{e}^{z}}\right)\) with \(\mathrm{J}\) categories of the variable. Regarding working time autonomy, the indicators of “Regular on-call or standby service”, “Make own decisions about breaks” and “Separation of work and private life possible” are subject to a binary logistic distribution, and the indicator of accessibility in private life is subject to a multinomial logistic function. All variables regarding “Muscular and skeletal strain” and “Strain from the working environment” are binary coded and accordingly follow a binary logistic distribution. To take into account that the assignment of employees to critical and noncritical jobs might not happen randomly, we obtained cluster-robust standard errors for 144 occupational groups of the German Classification of Occupations 2010 from the regression analyses.

To check the robustness of our results regarding the categorisation of critical jobs, we re-estimated our analyses with two different classifications (see Sect.  5.4 ), both of which have been used in empirical research investigating critical jobs in Germany. The first one of Koebe et al. ( 2020 ) comprises the list of essential frontline workers of the federal state of Berlin compiled at the onset of the coronavirus pandemic at the less differentiated three-digit level of the classification of occupations. The second re-estimation was carried out on the basis of the 88 divisions of the German Classification of Economic Activities 2008 (Federal Statistical Office 2008 ) and represents the original KRITIS list without coronavirus-conditional modifications. The KRITIS list was the starting point for all classifications of critical jobs and has been applied to analyses of the corona pandemic by Lübker and Zucco ( 2020 ). This list is comparatively narrowly defined and includes, in particular, sectors and occupations needed in the short term to provide basic services to the population. This operationalisation of jobs as critical can be found in Pfeiffer ( 2020 : 68; fifth column).

5.1 Descriptive results

Among the 31.8 million employees in our analysis sample, 17 million, or 53%, work in a critical job (Fig.  1 ). Furthermore, critical jobs are found to varying degrees in the different sectors of the economy. Such jobs comprise comparatively small shares of the agriculture and manufacturing (39.8%) and financing and business services (44.9%) sectors. A total of 52.7% of critical jobs are observed in the trade, transport and hospitality sector; the highest share of critical jobs is in the public and private services sector (71.7%).

Share of critical jobs (in percent). Source: Working Time Survey 2019; own calculations

On average, employees in Germany earn 19.52 euros (Table 1 ). Employees in critical jobs are paid 18.74 euros per hour, slightly less than those in noncritical jobs, as the latter are paid 20.19 euros per hour. Among the ten lowest-paid critical occupations are cleaning services, (retail) sales occupations selling foodstuffs and doctors’ receptionists and assistants (Table 2 ).

Furthermore, Table 1 shows that approximately 76% of all jobs involve physically proximate activities. Compared to employees in noncritical jobs, those engaged in critical jobs are 17 percentage points more likely to work physically proximately to others. Home office work, which ensures distance from others while working, can be performed by 20% of employees; however, this proportion is significantly lower for essential employees (12%) than for nonessential employees (26%). Regarding the duration of work, weekly overtime is slightly higher among those in critical jobs (3.33 h compared to 3.14 h). Shift work and night work represent atypical working hours. In this respect, normal working hours during the day (between 07:00 and 19:00) are less common in critical jobs (63%) than in noncritical jobs (77%); however, rotating shifts without and with night work are approximately 4 and 9 percentage points more common in critical jobs, respectively. There are also crucial between-group differences with regard to weekend work. Working on both Saturdays and Sundays is much more common among essential employees (33%) than among nonessential employees (15%). Working time autonomy is lower among essential employees because they are more regularly on call or on standby than are nonessential employees (13% compared to 6%) and are less able to make decisions about their breaks themselves (37% compared to 30%). In addition, essential employees are expected to be accessible for work-related matters in their private lives more often. Regarding muscular and skeletal strain, essential employees more often perform their work in a standing position (63% compared to 45%) or in a kneeling, bending, or overhead position (19% compared to 14%) and must lift and carry heavy loads more often than other workers (26% compared to 16%). Strain from the working environment, such as working under bright, poor or faint light or in cold, hot, wet, damp or draughty conditions, is more frequently reported by essential employees (15% and 29%) than by other employees (9% and 20%).

Given the great importance of critical jobs for the economy, first, the sociodemographic, job-related and structural determinants of employment in critical jobs are assessed; second, the working conditions in those jobs are examined.

5.2 Determinants of working in a critical occupation

The probability of performing a critical job, presented in Table 3 , is determined based on three estimations, into which the explanatory variables are added sequentially. Footnote 5 Model 1 contains sociodemographic and household characteristics, model 2 adds job-related factors, and model 3 includes structural determinants as well as occupational information. A comparison across the results of models 1, 2 and 3 reveals that the inclusion of the additional variable blocks in models 2 and 3 causes some significant correlations with sociodemographic and household characteristics to become insignificant.

According to model 3, there are no gender differences in the probability of working in a critical job. While there is no statistically significant correlation with age, East German workers are more often observed in critical jobs. The results indicate a lower probability of being employed in a critical job for workers without a vocational degree. Overall, the results on household characteristics do not display significant correlations.

Regarding job-related factors, it is evident that the probability of being an essential employee rises with increasing tenure. The opposite is the case for workers in marginal employment. While the type of contract does not have any significant influence on this probability, the complexity of the job plays a role. In particular, employees who perform complex specialist activities or highly complex activities work in critical jobs significantly less often than employees in unskilled or semiskilled activities. The latter also applies to employees who have an additional job. Regarding structural factors, we find that critical jobs are performed more frequently in medium-sized companies (those with between 10 and 49 employees). Employees in companies that do not have a work council are less likely to engage in critical jobs. Relative to the probability in the occupational segment of manufacturing, the highest probabilities of working in a critical job exist in the cleaning, transport and logistics, medical and nonmedical health care and IT and natural science services segments.

5.3 Working conditions in critical jobs

To identify risk factors in critical jobs, the following analyses examine wages, physical proximity to others at work, working time patterns and physical working conditions. Due to the different scales of the dependent variables, we estimate various multiple regressions. The corresponding functional form—linear, binary logistic or multinomial logistic estimation—is indicated in the tables.

The first crucial dimension of working conditions is wages. We perform Mincerian regressions on logarithmically transformed hourly wages and control for sociodemographic, job-related and structural factors. Footnote 6 The central variable of interest, the dummy indicator for whether a job is critical or not, is significantly negative (Table 4 ). This coefficient implies that essential employees earn 2.08% lower wages than nonessential employees. Footnote 7

The second important dimension of working conditions during the COVID-19 pandemic is the degree of physical proximity to others at work (Table 5 ). Employees in critical jobs have a 13.2 percentage-point higher probability of performing a physically proximate job than nonessential workers. They are, on the other hand, 6.2 percentage points less likely to have the opportunity to work from home.

The third dimension of working conditions is working time patterns. Table 6 presents the results for the duration of work and atypical working hours. Employees in critical jobs work overtime significantly more often. In addition, essential employees have a higher probability of working early or late shifts, rotating day shifts and shift and night work. With regard to weekend work, there are no differences in the probability of working on Saturdays; however, essential employees are more likely to work on Sundays.

Disadvantageous job characteristics are also apparent when we consider working time autonomy (Table 7 ). Critical jobs are more likely to be associated with regular on-call or standby service. Furthermore, essential employees report being able to decide on their breaks by themselves comparatively less often than other workers. The expectations of superiors and colleagues that workers are accessible in their private lives are higher in critical jobs. Finally, essential employees have a lower probability of finding it possible to separate work and private life.

The last dimension examined concerns physical working conditions. With regard to muscular and skeletal strain, critical jobs are performed in a standing position significantly more often but in a sitting position less frequently than other jobs (Table 8 ). Additionally, essential employees work more often in a kneeling or bending position or above their heads. They also have to lift and carry heavy loads more frequently.

Concerning strain from the working environment, essential employees report significantly more often that they do their job in noisy conditions; in bright, poor or faint light; and in cold, hot, wet, damp or draughty conditions (Table 9 ). Moreover, they can less frequently influence the work tasks that must be carried out than their nonessential counterparts.

5.4 Robustness checks

To check the robustness of our results regarding the categorisation of critical jobs, we re-estimated the determinants of critical occupations and their working conditions in two ways. First, we used the alternative three-digit level classification of first-hour occupations from Koebe et al. ( 2020 ), which focuses more narrowly on frontline work. Footnote 8 Second, we employed the operationalisation of critical sectors from the original KRITIS list without the COVID-19-conditional modifications, which is also comparatively narrowly defined (Pfeiffer 2020 : 68). Footnote 9

The basic descriptive results reveal marked differences. While the classification of Burstedde et al. ( 2020 ) identifies 53.48% of jobs as critical, the figures are considerably smaller when we use the three-digit classification of Koebe et al. ( 2020 ) (41.3%) or the original KRITIS list (40.9%). This indicates that the classification of Burstedde et al. ( 2020 ) identifies more than just frontline workers and considers the value chains more broadly than the KRITIS list, which specifies a limited number of sectors and occupations needed in the short term to provide basic services to the population.

The robustness tests for the determinants of working in a critical job accordingly show differences associated with the use of both the narrower definitions of critical labour (Additional file 1 : Appendix Table A3). The frontline work categorisation of Koebe et al. ( 2020 ) is characterised more significantly by female employment, younger workers and those with a technical school or master’s degree. Part-time workers, those performing a specialist activity and those holding an additional job work more often in critical jobs. Footnote 10 In contrast, the KRITIS classification points to a lower probability of carrying out a critical job for workers in East Germany and those with a vocational, technical school or master’s degree. This also applies to employees who have children. The form of employment, holding an additional job, the size of the company or the existence of a work council have no impact. The results of the robustness checks on working conditions in critical jobs (Additional file 1 : Appendix Table A3) based on the classification by Koebe et al. ( 2020 ) differ from our main results and become nonsignificant regarding weekly overtime, early or late shift work, the expectation of superiors and colleagues that workers are accessible in their private lives, the separation of work and private life and most variables related to physical strain from the working environment. Under the KRITIS operationalisation, almost none of the indicators of wages, physical proximity to others at work, duration of work and atypical work hours, or working time autonomy are related to employment in a critical job. Overall, the robustness checks for the determinants of working in a critical job indicate that the findings of which worker characteristics are determinant depend on the group definition used.

Regarding working conditions (Additional file 1 : Appendix Table A4), use of the two coronavirus-specific classifications from Burstedde et al. ( 2020 ) and Koebe et al. ( 2020 ) reveal disadvantages in terms of wages and higher physical proximity to others in critical jobs. Such jobs are also associated with more atypical working hours and less working time autonomy. Workers in such jobs are more affected by muscular, skeletal, and environmental strains from their working positions, carrying of heavy loads and exposure to noise levels. However, under the KRITIS classification, which focuses on basic services to the population and does not include sectors or occupations of major importance during the COVID-19 pandemic, the results are very strongly divergent. This suggests that the KRITIS list is of only limited validity for studies on the COVID-19 pandemic.

6 Discussion of results

The COVID-19 pandemic has had a strong impact on various dimensions of social inequality in the labour market and on work-related strains. This seems to be particularly the case for employees in systemically relevant occupations (Blau et al. 2020 ; Lübker and Zucco 2020 ; Koebe et al. 2020 ) that ensure the maintenance of critical infrastructure and the provision of medical care and nursing services and the supply of essential goods. Such employees were asked by political actors and the general public to continue working despite the health risks arising from the pandemic. These special circumstances increased the public’s awareness of essential occupational groups and raised questions surrounding the conditions under which essential employees work. However, only three quantitative analyses on this topic have been available to date (Blau et al. 2020 ; Lübker and Zucco 2020 ; Koebe et al. 2020 ) and have provided inconsistent results regarding working conditions in critical jobs due to data restrictions and the analyses’ mainly descriptive character. Against this backdrop, this study performed a more comprehensive analysis of working conditions in critical jobs. We were able to expand on previous research in three ways.

First, regarding data and methods, we used the representative German Working Time Survey 2019 to conduct our empirical analyses. These data allowed us both to identify critical jobs and to examine four dimensions of working conditions. The data were collected before the COVID-19 pandemic hit Germany, which ensures that the comparison groups and the variables of interest were unaffected by the pandemic. Furthermore, jobs could be classified at the 5-digit occupational level based on the classification of Burstedde et al. ( 2020 ), which made possible a differentiated categorisation of occupations by their systemic relevance during the COVID-19 pandemic. Our rich dataset allowed us to move beyond the descriptive evaluations that have predominated to date, identify working conditions through multiple estimations, and control for a variety of sociodemographic, job-related and structural factors.

Second, in terms of content, our descriptive findings indicated that 53.48% of employees in the survey sample worked in a critical job. Our multiple regressions revealed that employees living in East Germany and those with longer job tenure more often worked in critical jobs. Critical jobs were more often located in medium-sized companies and in companies with a work council. Furthermore, critical jobs could be found in the cleaning, transport and logistics, medical and nonmedical health care and IT and natural science services segments, a finding in line with those of Blau et al. ( 2020 ) and Koebe et al. ( 2020 ).

Third, regarding working conditions, our descriptive analyses showed that essential employees earned on average 18.74 euros per hour (gross) and thus 1.45 euros less than other employees. Among the lowest paid critical occupations were those in cleaning services, (retail) sales occupations selling foodstuffs and doctors’ receptionists and assistants. The multiple estimates confirmed our descriptive findings and the previous findings of Blau et al. ( 2020 ) and Koebe et al. ( 2020 ) that essential workers receive lower wages. Furthermore, essential employees were 13.2 percentage points more likely to work in jobs requiring physical proximity to others and could do home office work significantly less often. Both findings accord with recent research on the correlation between critical work and physical proximity (Avdiu and Nayyar 2020 ; Dingel and Neiman 2020 ). Concerning working time patterns, critical jobs were associated with overtime work and atypical working hours (day and night shifts and Sunday work) significantly more often than other jobs and involved a lesser degree of working time autonomy due to requirements to regularly be on call or standby, higher expectations for accessibility in private life, fewer opportunities to make decisions about breaks and an impossibility of separating their work and private life. With regard to physical working conditions, our estimates indicated exposure to greater muscular and skeletal strain in critical jobs because workers had to work more frequently in a standing, kneeling or bending position or in overhead activities and because of the requirement to lift and carry heavy loads. Finally, we revealed greater strain from the working environment (noisy conditions; bright, poor or faint light; cold, hot, wet, damp or draughty conditions; and the inability to influence one’s work tasks) in critical jobs.

Fourth, the theoretically basis of our research on systemically relevant jobs referred to approaches to human resource management that explain labour market segmentation (Hendry 2003 ; Osterman 2011 ; Kaufman 2013 ). According to these approaches, employees are particularly likely to occupy unfavourable positions in the labour market when they have little power to act, which can be explained by access to resources such as professional knowledge and skills or by the specificity of their learned profession, legal regulations, collective agreements, or internal institutions such as work councils (ibid.). While we did not discover educational differences between essential and nonessential employees (the former even had longer work tenures), we did observe higher probabilities of working in critical jobs among employees performing unskilled or semiskilled activity, who have also been found to occupy inferior positions in the employment system in other research (Lucifora and Salverda 2009 ; Howell and Kalleberg 2019 ). Furthermore, essential employees reported a comparatively higher prevalence of work councils. Thus, except for the distribution of workers carrying out unskilled or semiskilled activity, the sociodemographic and structural determinants of interest in our research did not reflect the crucial characteristics of employment in unfavourable labour market positions. However, a closer look at the occupational segments indicates that critical jobs are often located in sectors with little or no collective bargaining coverage, such as security, cleaning, transport and logistics and retail and trade (Ellguth and Kohaut 2019 ). Finally, our findings on working conditions align with research on segmented labour markets (Kalleberg 2011 ; Osterman 2011 ; Kaufman 2013 ). In fact, the risks of significantly lower wages, higher physical proximity to others at work, longer working hours, more atypical working hours, less working time autonomy and greater muscular and skeletal strain and strain from the working environment tend to accumulate in critical jobs.

7 Conclusions

The COVID-19 pandemic has focused public attention on occupational groups that are highly important to the functioning of social life. Our empirical analyses highlighted that risks resulting from working conditions in critical jobs do not occur separately but cumulatively, which leads to severe health risks, as the cited literature has revealed. This accumulation of risks already characterised such jobs before the pandemic. However, these unfavourable working conditions were exacerbated by the fact that the pandemic has aggravated existing strains.

A possible beneficial federal measure would be to define the group of critical jobs more precisely. As our robustness checks showed, the sociodemographic, job-related and structural characteristics related to critical jobs changed according to the definition of critical jobs used. A formal list based on common industry codes or occupational classifications could be used to better prioritise safety measures, provision of protective equipment and other targeted benefits.

A further and already well-known public policy implication is related to occupational wage inequality. Our findings indicated that critical jobs are predominantly low-paid occupations in sectors with low collective bargaining coverage. Therefore, a longer-term measure would be to increase collective bargaining coverage in these sectors of the economy to raise the attractiveness of critical jobs. Because simply showing up to work has put many essential workers at risk, the high physical proximity to others and the associated risk of infection make it necessary to provide frequent COVID-19 tests and to cover hospitalisation and health costs.

Work-related strains from long and atypical working hours and physically demanding work increased during the COVID-19 pandemic since the labour of essential employees was required on a larger scale and with greater intensity than before. Physical stress could be reduced by allowing regular rest breaks during the working day. The health risks associated with long and atypical working hours could be reduced by adhering to daily maximum working hours and requiring recovery phases between shifts in critical jobs. Such a balance of service provision and staff safety is all the more necessary to prevent burnout and insomnia under the increased workloads caused by the COVID-19 pandemic. To maintain the working capacity of this highly strained group of employees, the work-related disadvantages and strains of close physical proximity to others, heavy physical demands and inconvenient working time patterns need to be addressed as a whole through different measures, as physical exhaustion often leads to individual failures to comply with occupational health and safety measures.

Availability of data and materials

The Scientific Use File of the BAuA Working Time Survey 2019, Version 1 (1048697/baua.azb19.suf.1) can be obtained from the BAuA research data centre ( https://www.baua.de/DE/Angebote/Forschungsdaten/Arbeitszeitbefragung.html ).

The first-hour critical occupations consist of those corresponding to activities considered systemically relevant since the beginning of the coronavirus crisis.

The German classification of occupations (KldB 2010 ) comprises five digits: the first four digits categorise occupations on a horizontal dimension according to the area of expertise; the fifth digit groups occupations on a vertical dimension according to four requirement levels and, thus, the complexity of the tasks performed. The first digit level consists of 10 occupational areas, the second of 37 occupational main groups, the third of 144 occupational groups, the fourth of 700 occupational subgroups, and the fifth of 1,286 occupational types. Another aggregation level covers 14 occupational segments, which are used in the following regression analyses in Table 3 to characterise critical occupations.

There are currently almost 28,000 different occupational titles in Germany. In addition to the common, current occupational and task designations, these also include synonyms and related forms of these designations, precursor occupations, former GDR occupations and other common designations relevant to the labour market. These individual positions are kept by the Federal Employment Agency (BA) in an occupational database and are clearly assigned to an occupational type of the KldB ( 2010 ) classification.

The value 4.33 denotes the average number of weeks per month.

Descriptive statistics on the explanatory variables are provided in the appendix (Additional file 1 : Appendix Table A2).

The complete regression results for models 4 to 9 can be obtained from the authors upon request.

Since the regression coefficients indicate log points, these can be transformed into percentages by using the formula \(\left({e}^{\beta }-1\right)*100\) .

The alternative three-digit level classification of first-hour occupations by Koebe et al. ( 2020 ) does not especially contain occupations in farming, animal husbandry, fishing, underground and surface mining, plastic- and rubber-making and -processing, paper-processing and packaging, precision mechanics, machine-building and -operating, the automotive, aeronautic, aerospace and ship building industries, energy technologies, electrical engineering, the production of clothing and other textile products, the production of foodstuffs, water resource management, civil engineering, building services engineering, plumping, sanitation, heating, ventilating, and air conditioning, biology, chemical and pharmaceutical engineering, environmental protection management, software development and programming, drivers and operators of construction and transportation vehicles and equipment, occupations in medical documentation, teachers in schools of general education, editors and journalists, and technical occupations in video and sound production. In contrast to the classification by Burstedde et al. ( 2020 ), the categorization by Koebe et al. ( 2020 ) primarily additionally includes occupations in plant, vessels, tank and apparatus construction, sales occupations (retail trade) selling office supplies, gifts and toys, gastronomy occupations, occupations in recruiting and employment services, insurance and financial services, tax consultancy, non-medical animal health practitioners, and occupations in non-medical therapy and alternative medicine.

The KRITIS list does not especially include occupations in public administration, biology, chemistry, cooking occupations, doctors’ receptionists and assistants, drivers of vehicles in road traffic, occupations in editorial work and journalism, transport and logistics, occupations in legal services, jurisdiction, and other officers of the court, IT-network engineering, IT-coordination, IT-administration and IT-organisation, occupations in education and social work, and pedagogic specialists in social care work, nursing, emergency medical services and obstetrics, physical security, personal protection, fire protection and workplace safety, teachers in schools of general education, occupations in cleaning services, building services engineering, funeral services, geriatric care, electrical engineering, technical occupations in energy technologies, occupations in purchasing and sales, plumping, sanitation, heating, ventilating, and air conditioning. This list additionally contains sales occupations in retail trade, occupations in non-medical therapy and alternative medicine, gastronomy occupations, media, documentation and information services, advertising and marketing, business organisation and strategy, accounting, controlling and auditing, and purchasing and sales. Generally, the disadvantage of the KRITIS list categorization is that it excludes entire sectors of the economy with occupations that are critical or includes entire sectors of the economy even though they contain occupations that are not critical.

Since this classification is based on three-digit occupations, occupational segments could not be included in the estimation due to multicollinearity.

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Additional file 1..

Appendix: Table A1 : Critical occupations according to Burstedde et al. (2008: 27ff.). Table A2 : Descriptive statistics for explanatory variables. Table A3 : Robustness checks of the determinants of working in a critical job (logistic regressions). Table A4 : Robustness checks for working conditions in critical jobs.

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Dütsch, M. COVID-19 and the labour market: What are the working conditions in critical jobs?. J Labour Market Res 56 , 10 (2022). https://doi.org/10.1186/s12651-022-00315-6

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