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The effect of COVID-19 on employees' mental health
- Didem Rodoplu Şahin ORCID: orcid.org/0000-0002-1779-8472 1 ,
- Mustafa Aslan ORCID: orcid.org/0000-0001-8049-3615 2 ,
- Harun Demirkaya ORCID: orcid.org/0000-0003-0260-7538 1 &
- Hülya Ateşoğlu ORCID: orcid.org/0000-0003-2116-3821 2
Scientific Reports volume 12 , Article number: 15067 ( 2022 ) Cite this article
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Long lockdowns, food shortages, and the inability to receive basic primary healthcare have aggravated the effects of pandemics. However, most studies have focused on the health problems of the infected people or the measures employed to keep the disease under control. This cross-sectional study focused primarily on the mental health issues of employees. By employing a convenient sampling method, we reached 237 respondents (135 with coronavirus history) to assess the impact of the pandemic on employees. Multivariate causal relationships were assessed with Structural Equation Modeling (SEM). The predictors included internal entrapment (INT) and difficulty identifying feelings (DIF), which are significant predictors of depression (DEPR). DIF was found to be a significant predictor of INT and EXT feelings, while FEAR was found to be a significant predictor of INT, DIF, and DEPR. Quality of life (QoL) was found to be a significant predictor of DIF and DDF, DEPR, EXT and INT, and FEAR. The results also showed that DIF mainly manifested its effect on depression through INT. The DEPR level of employees working only from home was higher than that of other employees. The depression levels of women, young employees, and those whose QoL was adversely affected by the coronavirus were higher than the rest.
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Acute psychological effects of Coronavirus Disease 2019 outbreak among healthcare workers in China: a cross-sectional study
Introduction.
The COVID-19 pandemic, which emerged in December 2019, caused a public health crisis worldwide. On July 28, 2022, the number of confirmed cases was over 571 million, and the death toll was over 6.3 million worldwide 1 ; these figures continue to rise steadily every day. The situation was not different in Turkiye, with over 15 million confirmed cases and around one hundred thousand deaths due to the coronavirus between March 2020 and May 2022 2 . This situation has created a sense of threat and concern that has spread at an alarming rate over the world 3 . Due to COVID-19, millions of people were locked down for weeks, lost their jobs, and, most importantly, their loved ones. In short, COVID-19 has had an impact on all aspects of our lives, from financial to social interactions, family to business relations, and physical to mental health, especially healthcare workers who have been fighting coronavirus at the frontline 4 , 5 , and older adults 6 .
Many COVID-19 patients show signs of post-traumatic stress disorder (PTSD). Employees suffering from PTSD are more likely to suffer from other mental health concerns and lose their ability to focus on cognitive activities. The three main clusters of PTSD symptoms (avoidance, intrusion, and hyperarousal) were proved to be substantially predicted by high levels of alexithymia, dissociation, anxiety, and sadness in persons who had recovered from COVID-19 7 . People who suffer from PTSD harbor frequent intense, distressing thoughts and feelings related to their traumatic experience. They may be stricken with grief, fear, or rage or feel isolated or disconnected from others 8 . They are also more likely to have alexithymic characteristics 9 , which means they can think, act, communicate, and perceive emotions but fail to correlate them with the related feelings, i.e., disconnection of the body and mind. In the absence of communication between the mind and the body, a state of body-mind dissociation ensues, which might be a sign of a protective mechanism or an alexithymic disorder 10 .
Moreover, the pandemic increased the risk of PTSD. According to Total Brain and the National Alliance of Healthcare Purchaser Coalitions 11 , the risk of PTSD has climbed month over month and, as of June 2022, is 51% greater than in the pre-pandemic era. According to the measure, nearly one-fifth of employees were at risk of having PTSD.
Alexithymia is a Greek word that means " absence of words for emotions " 12 . People suffering from this disorder have problems establishing a correlation between their feelings and thoughts and expressing them 12 . People with alexithymia typically struggle to recognize and express their emotions, display emotional functions, and establish interpersonal relationships 13 . Alexithymia has three dimensions: (1) difficulty in identifying feelings and distinguishing them from bodily sensations (DIF); (2) difficulty in describing feelings and putting them into words (DDF); (3) externally oriented thinking (EOT) 14 . The dimensions associated with identifying (DIF) and describing (DDF) feelings are positively related to depression and anxiety 15 , 16 , 17 , 18 .
Entrapment, on the other hand, is the desire to leave an unpleasant or challenging circumstance or uncertainty while also feeling compelled to avoid the unpleasantness of unease. When an individual is subjected to prolonged stress or has his or her conduct restricted by internal or external circumstances, he or she is said to be entrapped. Feeling entrapped in all aspects of life can have a negative impact on one's self-development and interpersonal relationships, either directly or indirectly 19 . Furthermore, when a person feels impotent to modify his or her circumstances, he or she is more likely to develop mental health issues. The experience of entrapment can be caused by a variety of factors, which the research categorizes as internal and external aspects 20 , 21 . During COVID- 19, people all around the world have had more than their fair share of suffering from feelings of entrapment 22 .
During the COVID-19 pandemic, many people died, and many went through traumatic experiences. Despite the fact that the number of confirmed cases is limited to barely 3.5% of the world's population, the coronavirus outbreak has caused increased fear and trauma due to widespread media coverage. Prolonged lockdowns, both qualitative and quantitative job insecurities and unemployment due to downsizing or bankruptcies 22 , shortage of food, inability to receive basic healthcare, fear of death, or causing the death of a loved one were primary factors are worsening the trauma. The outbreak, which rendered many people unable to think, act, or react 24 , 25 , has become this generation's worst frustrating experience. People were unable to avoid this predicament despite their best efforts 20 , 21 . They felt helpless 26 , 27 and defeated 28 , no matter the measures were taken against the disease.
Although symptoms and the effects of coronavirus on health have been excessively covered by media 29 , many people, including healthcare workers, experienced vaccine hesitation due to a lack of confidence in the vaccines 30 , 31 . Moreover, misinformation spread through social media 31 , and being exposed to them due to the overuse of electronic devices during the lockdowns left people anxious, fearful, and ultimately hopeless 32 . Furthermore, the lockdown and other measures to keep the disease under control restricted people's engagement in physical and social activities, making them vulnerable to a higher risk of physical and physiological problems 33 .
Despite the pandemic's highly unfavorable impact on public health, most of the research on the COVID-19 pandemic has been mainly on infected people's health issues or the impact of lockdowns or other measures used to keep the disease under control. Although every adult is either an employee or has at least one employee in their household, there has been almost no research comparing the mental health of infected and uninfected employees and examining the impact of the pandemic as a whole (not only the steps taken to prevent the spread of coronavirus but also the fear experienced by individuals).
Hence, this study aims to investigate the effect of COVID-19 on employees' mental health by assessing the effect of coronavirus-caused fear on identifying and describing feelings dimensions of alexithymia and of entrapment on depression level of employees. Although workers of some sectors, especially the health care sector, are exposed to COVID-19 more than any other sector, this study does not focus on a specific sector, gender, or age group.
Study design
The questionary consists of five parts. The questions in the first part were about the demographics of the participants, such as age, gender, and workplace during the pandemic (e.g., from home, both from home & workplace, and only from the workplace).
The second part incorporated a questionnaire including the following questions: "Have you lost any relatives or close friends due to coronavirus?", "How did the COVID-19 pandemic affect the quality of your life?", and "What would you fear most if you had been infected with coronavirus?" In the third part, we used three different scales: (1) the Turkish version of the Toronto Alexithymia Scale (TAS-20) 34 to measure identifying and describing feelings , (2) the 21-item Beck Depression Inventory-II 35 , and (3) the entrapment scale developed by Gilbert and Allan 36 . The scores of the Beck Depression Inventory-II were interpreted as suggested by Smarr and Keefer 37 .
Because the current scales have not been measuring the fear of infecting and causing the death of other people, especially relatives and loved ones, the authors have to create their own scale. The scale had a total of five items, and the respondents were asked to rate the five items from 1 to 5 (From the lowest to the highest, the level of fear is ranked from 1 to 5). The exact same questions were asked to both groups but with different tenses (e.g., "I am afraid of dying" to uninfected, and "I was afraid of dying" to the employee with coronavirus history).
The five items were related with:
Afraid of being infected with the coronavirus.
Afraid of infecting one's own family members or loved ones.
Afraid of infecting people other than one's own family members and loved ones.
Afraid of losing someone because of transmitting the disease to him or her.
Afraid of dying.
The aim of asking the question, "How did the COVID-19 pandemic affect the quality of your life?" was to assess the participant's perception of the quality of life (QoL) during the pandemic. The options given to the question were (1) no effect; (2) minimal adverse effect; (3) moderate adverse effect; (4) very high adverse effect.
Participants marked (0) if they had not lost any relatives or close friends, (1) for one relative or close friends, and (2) for more than one relative and close friends.
Data collection
This cross-sectional study was conducted in the Istanbul province of the Republic of Turkiye between September 26 and October 15, 2021. We reached the participants through social media and sent the questionary links (a total of two links; one for those with coronavirus history and one for those having no history) to those who volunteered to participate in the study. To promote participation, the researchers undertook to donate to Darülşşafaka Society-a well-known NGO in Turkiye founded in 1863 to provide equality of opportunity in education to needy, talented children who had lost their fathers—and stated this undertaking in the introduction part of the questionary. Participants then shared the questionary in their networks.
Being an employee (18 years old or over) was required to take part in the study. 237 of the 243 collected surveys were included in the analysis. Six surveys were omitted because two of the participants were underage, and four were housewives and thus were not eligible to participate in the study. The participants' average age was 40.17. Table 1 shows the demographics of the participants.
This study is approved by the Kocaeli University Social and Human Sciences Ethics Committee (protocol number: E-10017888–108.99–62,960).
Data analysis
Confirmatory Composite Analysis, Convergence and Discriminant Validities, and Reliability Tests were performed. Partial Least Square Structures Equation Modelling (PLS-SEM) with SmartPLS version 3.2.9 is used for data analysis. The coefficient of determination (R-square) and the Q-square value (the prediction relevance) was used to assess the model's acceptability. SPSS version 26 was also used as deemed necessary. The Pearson correlation coefficient and significance levels used to interpret results of correlation analysis. Figure 1 depicts path analyses using the path model.
![research paper on impact of covid 19 on employees figure 1](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41598-022-18692-w/MediaObjects/41598_2022_18692_Fig1_HTML.png)
Path model. FEAR: Fear; LOC: Work Location; DEC: Decease of a Relative or Acquaintance; QoL: Quality of Life; DDF: Difficulty Describing Feelings; DIF: Difficulty Identifying Feelings; EXT: External Entrapment; INT: Internal Entrapment; DEPR: Depression Level.
Criteria for the validity and reliability are as follow:
For Convergence Validity:
The average Variance Extracted (AVE) value must be equal to or greater than 0.50 38 , 39 .
Composite Reliability (CR) value must be equal to or greater than 0.70 and the square root of the AVE value 38 , 39 .
Cronbach Alpha value must be equal to or greater than 0.70 38 , 39 .
For Discriminant Validity:
Heterotrait-Monotrait Ratio (HTMT) Values have to be 0.90 for the theoretical concepts close to each other and 0.85 for those that are distinct 40 .
Variance Inflation Factor (VIF) value must be below 5 41 .
For model acceptability:
The coefficients of determination (R 2 ), which implies the model's goodness-of-fit for the dependent variable, must be greater than 0.10 39 , 42 .
The Q 2 value (the prediction relevance) has to be greater than zero 43 .
Furthermore, factor loadings have to be equal to or greater than 0.70. and the items with factor loadings below 0.40 have to be excluded from the analysis. Items with factor loadings between 0.40 and 0.70 will be kept in the model if CR and Cronbach Alpha values of the construct are over the threshold 39 .
Background of the study
A close friend of one of the article's authors called in and asked for assistance about quitting his job. Following a discussion on how he felt, he appeared to be perplexed and had difficulty articulating and expressing his emotions. Afterwards, the author interviewed approximately 20 persons with coronavirus history, and observed similar symptoms with majority of them. Especially those experienced the coronavirus severely had difficulty with describing and expressing their feelings. Most of them described the situation they are in as "I feel like I'm being suffocated." Based on their observations, the authors designed this study to investigate the possible effect of coronavirus on alexithymia, entrapment, and depression.
Ethical approval
This study is approved by the Kocaeli University Social and Human Sciences Ethics Committee (protocol number: E-10017888-108.99-62,960).
Human and animal rights
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent
Informed consents were obtained from all individuals participated in the study.
Results and discussion
After performing Confirmatory Composite Analysis (CCA), the factor loading of item number 11 of the TAS-20 was found to be less than 0.40 and removed from the model. The final run's Cronbach's Alpha, CR, and AVE values (Table 2 ) confirmed that the scales collectively satisfied the internal consistency reliability and convergent validity conditions.
The highest HTMT value was measured as 0.751 < 0.900 between INT and EXT, and VIF as 2.817 < 5.000 between INT and DEPR. Therefore, we concluded that the scales satisfied the discriminant validity condition, and no collinearity was observed between variables.
The coefficients of determination (R 2 ), which imply the model's goodness-of-fit, and Q 2 value (the prediction relevance), were measured and reported in Table 3 .
The results reported in Table 3 show that the Q 2 and R 2 values meet the criteria. Hence, it was concluded that the measurement model was acceptable.
Following the verification of the validity, reliability of the scales, and the measurement model's acceptance, The Partial Least Squares Structural Equation Modeling (PLS-SEM) and path analysis were used to test the structural equation model. In the analyses, using the bootstrapping method, 5,000 sub-samples were taken. The path coefficients (β values) and statistical significance ( p values) of the effects were calculated and reported in Table 4 (only significant effects included in the table, full table provided as supplementary resource). The total effects were also calculated and reported in Table 5 .
As per the results reported in Tables 4 and 5 , Depression (DEPR) was increased mainly by Internal Entrapment (INT), Difficulty Identifying Feelings (DIF), and Quality of Life (QoL), but Difficulty Describing Feelings (DDF) reduced it. INT was mainly affected by DIF, QoL, and FEAR. FEAR was mainly affected by QoL, DIF by QoL, FEAR, and Decease of a Relative or Acquaintance (DEC), respectively, and External Entrapment (EXT) by DIF. Moreover, Quality of Life (QoL) was affected by work location (LOC).
When an individual's perceived quality of life is being affected adversely, it causes an increase in the difficulty of identifying feelings, fear, external and internal entrapment feelings, and ultimately depression. The perceived level of quality of life is affected by work location. The perceived quality of life of the individual working from home is better than those working only from a workplace.
The work location also affects the external entrapment (Table 4 ), which makes us think that the measures taken to prevent the spread of the pandemic cause employees working only from the workplace to feel trapped in a situation they cannot escape. Interestingly enough, the work location did not have a significant effect on employees' fear. Upon not being able to observe any effect of work location on fear, we took a step forward and performed a correlation analysis. Still, we could not determine any correlation (r = − 0.043; p = 0.516). Normally working at the workplace, which requires being among crowds (especially during the rush hour commutes) every day, should have caused employees to develop a certain level of fear of contracting coronavirus and transmitting it to other people, whether they be family members or others. However, the results of our study showed the other way around, i.e., the fear of coronavirus has no relation to the workplace.
The average fear is measured as 4.0153 out of 5 point scale. As per descriptive statistics given in Table 6 , the highest fear employees experienced was causing someone else's death because of transmitting the disease to him or her (M = 4.4153), and the lowest was dying (M = 2.7089).
The mean differences of the following items were statistically significant compared to those with coronavirus history:
Afraid of infecting his/her family members or loved ones (ΔM = 0.30; p = 0.044)
Afraid of causing the death of someone else because of transmitting the disease to him or her (ΔM = 0.51; p = 0.001).
In both items, the average was higher for employees with coronavirus history. Nevertheless, the mean difference of the overall fear was not statistically significant (p = 0.112). The mean differences among work-location groups were not statistically significant either.
Although the work location did not have a statistically significant effect on fear, it had a significant effect on difficulty identifying feelings (β = 0.138; p < 0.01) and on external entrapment feeling (β = -0.137; p < 0.05). Working only from home increases the feeling of external entrapment, which should be quite a normal feeling since working from home may cause employees to develop a sense of isolation and entrapment 44 . The expectation, however, was quite the opposite since during the pandemic, home is generally considered a safe haven, while going out may be perceived as a threat.
Working only from home increases difficulty in identifying feelings. As can be found in the literature, working from home causes employees to develop negative feelings and agoraphobics 44 . The problem with the female employees working only from home reminds the problem described by Freidan[ 45 :11] in her book, The Feminine Mystique :
“American women have luxuries that women in other times and lands never dreamed of; part of the strange newness of the problem is that it cannot be understood in terms of the age-old material problems of man: poverty, sickness, hunger, cold. The women who suffer this problem have a hunger that food cannot fill.”
Female employees working only from home had everything they needed, as American women had, but the problem was feeling trapped in the house. For male workers, it is not exactly the same but similar; as Ahrentzen[ 44 :282] quotes from a homeworker, " It's difficult to detach from things at home. I must get physically away. [Man, Adults Only]. "
Another factor that increases the difficulty of identifying feelings is the loss of someone. Alexithymia is linked to a defensive mechanism that seeks to limit difficult, intense, and negative emotions and avoid terrifying or intolerable feelings 46 . When an employee loses his/her relative or close friend, this defense mechanism may enter the equation to protect the individual from the loss's painful, negative, or powerful feelings. In other words, the death of a loved one may trigger the defense mechanism, which may cause the person to have difficulty identifying feelings.
This study also showed that fear causes difficulty identifying and describing feelings. The isolation and feeling of loneliness experienced in the midst of the pandemic may lead us to recall the basic anxiety, for the conditions we experience during the pandemic resemble, if not identical to, those experienced during the basic anxiety. The basic anxiety is defined by Horney[ 47 :41] as " the feeling a child has of being isolated and helpless in a potentially hostile world. " This basic anxiety may also increase the use of this defense mechanism and fear. Fear, in return, may cause increased difficulty identifying feelings. Furthermore, on top of this pandemic situation that makes people feel entrapped 20 , the fear of infecting their families and others may cause the employees to develop anxiety, worry, helplessness, and uncertainty 48 . This fear may cause an increase in internal and external entrapment feelings, which is another finding of this study.
We also found that difficulty identifying and describing feelings, two dimensions of alexithymia that are closely associated with depression and anxiety 15 , 16 , 17 , 18 , also affect internal and external entrapment feelings. Furthermore, we believe this study also contributes to understanding the effect of alexithymia on depression. One possible mechanism is that difficulty identifying feelings increases internal entrapment, which in return causes an increase in depression. Although the literature is full of studies showing the relation of alexithymia with anxiety and depression, no study that links it to the feeling of entrapment exists. Therefore, the explanation that we have come up with maybe erroneous or have inadequacies. Being unable to identify feelings may cause employees to feel trapped inside because they could be capable of finding a solution or a way out if they were able to identify what they feel. That is why the difficulty identifying feelings has the highest effect (β = 0.582; p < 0.01) on inner entrapment feelings. This feeling of internal entrapment causes depression since it was found to be a significant predictor of depression (β = 0.614; p < 0.01). In their study carried out on 145 undergraduate students, Motan and Gençöz 49 came up with similar findings, concluding that internal entrapment is a significant predictor of depression and anxiety. The reducing effect of difficulty describing feelings on depression, on the other hand, is a subject that needs to be clarified.
As per the results given in Table 7 , no statistically significant differences were found between employees with and without coronavirus history. Furthermore, the mean depression score of employees with coronavirus history (M = 10.2444) is lower than the others (M = 11.5392), while this difference is not statistically significant (p = 0.326).
The mean depression score of employees working only from home (M = 14.0000) is higher than those working from both home and workplace (M = 9.3409) and only from the workplace (M = 10.6538) and this difference is statistically significant (F(2,234) = 3.421; p = 0.034). The depression score of employees working only from home shows that those employees suffer from mild depression symptoms.
The mean depression score of employees below the age of 21 (M = 26.5000) statistically (F(8,228) = 3.388; p = 0.01) differs from employees between the age of 31–35 (M = 8.9643), 41–45 (M = 7.8077), 46–50 (M = 8.8974), and 56-and above (M = 6.6190). Furthermore, personnel under the age of 21 exhibit moderate depression (M = 26.5000) symptoms, while those between the ages of 21 and 25 exhibit mild depression (M = 14.7778) symptoms.
The mean depression score of females (M = 12.6250) is higher than that of males (M = 8.3465), and this difference is statistically significant (p = 0.01). The mean depression score differences of employees whose quality of life was affected at moderate or very high levels were statistically significant (F(3,233 = 7.529; p = 0.000). Moreover, the depression score of employees whose quality of life was affected at a very high level (M = 17.0000) reveals that those employees are showing mild depression symptoms. The depression score of employees whose quality of life was affected at a moderate level (M = 13.2353) is at the edge of mild depression.
Multi-group analysis (MGA)
MGA was also performed to determine if the path model has statistically significant differences across demographic groups. The multi-group analysis allows researchers to reveal any significant differences in group-specific parameter estimates between pre-defined data groups (e.g., outer weights, outer loadings, and path coefficients). As suggested by Henseler et al. 50 , group comparisons using structural equation modeling (SEM) without establishing the invariance of composite models can be misleading 50 . Therefore, before conducting MGA, Measurement Invariance of Composite Models (MICOM) was assessed with its procedure in three distinct steps. The MGA may be performed on variables that have two groups. In our study, it may be performed only for gender and COVID-History variables.
The MICOM process was performed with SmartPLS 3.2 statistical software with 5,000 permutations, a two-tailed test type at 0.05 significance level, 1,000 maximum iterations, and a 10 –7 stop criterion. When running MICOM in SmartPLS, Step 1 of the procedure suggested by Hanseler et al. 50 is automatically confirmed 52 , 53 , 54 . Step 2 and Step 3 of MICOM were performed by a permutation test.
As per the results, full measurement invariance was found to exist in overall composites for both variables. The MGA is performed for both variables, and its results are reported in Table 8 .
According to Table 8 , the effect of the quality of life on depression, external entrapment, and difficulty identifying feelings was higher for employees with COVID-19 history. Fear had a more significant impact on internal and external entrapments in those not infected with the coronavirus. On the other hand, the effect of difficulty describing feelings on depression was higher for employees with a coronavirus history. These results suggest that the employees who have been infected with coronavirus feel less fear than those uninfected since they have experienced the coronavirus. This experience may have reduced the fear and entrapment caused by fear. However, the difficulty describing employees' feelings with coronavirus history was higher than in others. This finding is also supported by the findings of Ayaz and Dincer 55 .
Limitations
The findings of this study should be interpreted in light of its limitations. Because all of the data in this study came from the same source, it is susceptible to common method variance error. The Harman single-factor test 56 was performed to determine the magnitude of this error. The test result was 0.34973 (which is less than 0.50), which makes us conclude that the inaccuracy is acceptable. Another disadvantage of the study is that the interpretations and inferences may not be as precise or exact as intended because no comparable study has been detected in the literature.
This study also explored the history of infected and uninfected people, not the severity of their clinical course. Therefore, the results need to be interpreted accordingly.
Another limitation of this study has not differentiated participants based on their work area. Since not all workers were exposed to the same stress levels, the results may not be generalized for all sectors and should be interpreted cautiously.
This study is not longitudinal, but a cross-sectional study and the authors do not have pre-pandemic data of the participants. Therefore, the inferences related to alexithymia and its impact on the appearance of affective symptoms during the pandemic could result from previous personality traits or underlying mental disorders. Hence, the results should be interpreted accordingly.
Other drawbacks include using a convenience sampling strategy, relying only on self-reported measuring instruments, and carrying out the measurement only once. It may raise concerns about the findings' generalizability, selection bias, and causality inference difficulties.
Another drawback stems from the study's design. The data was acquired from the participants at a single point in time, and the researchers did not follow up with them over time. As a result, the findings should be carefully interpreted and validated through longitudinal research.
Implications for Practice
The dramatic spread of COVID-19 has disrupted lives, communities, and businesses alike. In their efforts to adapt themselves to the new challenges posed by the pandemic and mitigate the COVID- 19 impact, businesses were forced to find ways to help their employees stay in the work process as much as possible. Designing the workflow for employees in a way to enable them to work from home was one of the approaches by which many businesses responded to the coronavirus crisis. However, as revealed by this study, this approach or solution harbors an unforeseen and unrecognized consequence; it may cause employees to develop mental health problems.
As the study suggests, young employees and women who work solely at home are the two groups that suffer from mental health problems more than others. Proper conditions created in a workplace deeply motivate and engage employees and impact their mood, drive, and mental health. On the other hand, the home lacks such favorable features facilitating professional working and thus brings its own set of challenges that can negatively impact the mood when used as a workplace. Furthermore, working from home may cause the line between work and private life to get blurred. Expectations of other family members while working at home may leave female employees frustrated or feelings of unease, particularly at times when they fail to respond with the required reflex. Interruption of work with a ring at the door (to receive cargo, essential daily needs of the home such as drinking water etc.), technical problems (internet connection, computer problems that need the support of an IT person), personal calls, dropping by visitors/relatives sometimes extending their visit overnight and other unanticipated home situations also put a strain on the minds of employees and contribute to the undesirable atmosphere home offers for working.
As with the case of young employees (especially those under 21), the possibility of living with parents, and thus most probably, being unable to live in a home with physical conditions addressing to personal preferences and comfort, may cause distress while working from home. The presence of younger siblings who disrupt the working atmosphere with their nuisance or wishes, non-availability of a proper working space not accommodating the comfort office furniture provides, etc., may make young employees one of the groups suffering from mental issues more than others. Meanwhile, some young employees may also feel frustrated from being unable to express their inconvenient conditions at home to their employers. Being overwhelmed with the fear of the pandemic and thus feeling the urge to work at home, they may continue to work at home and feel its psychological pressure against all odds.
When these home-related inconveniences are kept in mind, businesses need to address all these mostly unrecognized issues to provide a favorable working atmosphere for their employees working only from home. Supporting the employees, whether by financial means or others deemed necessary, to improve their physical conditions at home will relieve them and make them feel less depressed, ultimately making them experience fewer mental issues.
Meanwhile, if possible, offering hybrid working conditions (working both from home and the workplace) or reducing the workload (including work hours) of those working only from home should be considered and assessed.
As well to young employees and female employees, employees with coronavirus history also seem to have higher mental health problems. The mental issues of the employees in these categories should be addressed by special care or particular policies.
On the other hand, working with psychologists or encouraging employees to visit psychologists, especially during the COVID-19 pandemic, maybe another solution for organizations. Finally, for those who experience mental health problems during the pandemic, organizations should be more flexible with their employees and amend their policies and key performance indicators accordingly.
The aim of this study was to investigate the effects of fear on identifying and describing feelings dimensions of alexithymia and dimensions of entrapment on the depression level of employees during the COVID-19 pandemic. The results show that internal entrapment and difficulty identifying feelings are the significant predictors of depression, whereas the difficulty identifying feelings is the significant predictor of internal and external entrapment feelings. Fear was the significant predictor of internal entrapment, difficulty identifying feelings, and depression. On the other hand, quality of life is a significant predictor of difficulties identifying and describing feelings, depression, external and internal entrapment, and fear.
The results also show that difficulty identifying feelings manifests its effect on depression mainly through internal entrapment.
This study also revealed that the depression level of the employees working only from home is higher than other employees. Moreover, the depression level of women, young employees, and those whose life quality was adversely affected by the coronavirus is higher than the rest.
Data availability
The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.
WHO (2022). WHO Coronavirus (COVID-19) Dashboard . https://covid19.who.int/ .
Turkish Ministry of Health (2022). Genel Koronavirus Tablosu. https://covid19.saglik.gov.tr/TR-66935/genel-koronavirus-tablosu.html
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Rodoplu Şahin, D., Aslan, M., Demirkaya, H. et al. The effect of COVID-19 on employees' mental health. Sci Rep 12 , 15067 (2022). https://doi.org/10.1038/s41598-022-18692-w
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The Impact of COVID-19 on Workers’ Expectations and Preferences for Remote Work
We study how COVID-19 affected the prevalence, expectations, and attitudes toward remote work using specially designed surveys. The incidence of remote work remains higher than pre-pandemic levels and both men and women expect this to persist post-pandemic. Workers also report increased preference for remote work as a result of the pandemic. These changes are strongly correlated with individuals’ exposure to the pandemic induced work-from-home shock, indicating that experience with remote work during the pandemic likely shaped expectations and preferences toward WFH. The magnitude of the effects on preferences and expectations are similar across gender, marital status, and presence of children.
We thank session participants at the ASSA Meetings for helpful comments. Funding from the Russell Sage Foundation is gratefully acknowledged. The views expressed in this paper do not necessarily reflect those of the Federal Reserve Bank of New York or the Federal Reserve System as a whole. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
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The pandemic has already dramatically changed the workplace landscape. Lockdowns and self-isolation have affected how people across the world are connected and working together. Employees had to learn to cope with these changes quickly. Teleworking, balancing work and life, dealing with technological ...
Keywords : Covid-19, Workplace practice, organizational communication, work-life balance, employee-manager relationship, organizational leadership
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Work From Home During the COVID-19 Outbreak: The Impact on Employees' Remote Work Productivity, Engagement, and Stress
Affiliation.
- 1 Department of Psychological, Health and Territorial Sciences, University "Gabriele d'Annunzio" of Chieti-Pescara, Chieti (Ms Galanti, Dr Guidetti, Ms Mazzei); Department of Psychology, Alma Mater Studiorum - University of Bologna, Bologna (Dr Zappalà, Mr Toscano), Italy; Department of Psychology and Human Capital Development, Financial University under the Government of Russian Federation, Moscow, Russia (Dr Zappalà).
- PMID: 33883531
- PMCID: PMC8247534
- DOI: 10.1097/JOM.0000000000002236
Objective: The COVID-19 pandemic made working from home (WFH) the new way of working. This study investigates the impact that family-work conflict, social isolation, distracting environment, job autonomy, and self-leadership have on employees' productivity, work engagement, and stress experienced when WFH during the pandemic.
Methods: This cross-sectional study analyzed data collected through an online questionnaire completed by 209 employees WFH during the pandemic. The assumptions were tested using hierarchical linear regression.
Results: Employees' family-work conflict and social isolation were negatively related, while self-leadership and autonomy were positively related, to WFH productivity and WFH engagement. Family-work conflict and social isolation were negatively related to WFH stress, which was not affected by autonomy and self-leadership.
Conclusion: Individual- and work-related aspects both hinder and facilitate WFH during the COVID-19 outbreak.
Copyright © 2021 American College of Occupational and Environmental Medicine.
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Conflict of Interest: nothing to declare.
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Technology Impacts on Employee Engagement During Covid-19
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This concept paper reviews the impact of communication and collaboration technologies (CCT) on employee engagement during the Covid-19 pandemic. The concept paper and arguments are based on academic research and will require future research to confirm the conceptual model and propositions. The Covid-19 pandemic is changing human interactions in the workplace. Leaders and employees are interacting virtually through CCT to maintain productivity and achieve business outcomes. Employee onboarding, virtual team engagement, and technology’s impact on employee engagement are the three emergent themes from the literature review on employee engagement, virtual teams, and human interactions in times of pandemics. Employee engagement, leadership engagement, and CCT are the three elements of successful virtual team engagement. Technology can positively and negatively impact employee engagement. Team building is the positive impact of technology on employee engagement with anxiety, cyberaggression, and video conferencing fatigue as the negative impact. It is critical to understand virtual employee engagement and the impact of CCT on that engagement to propose practical leadership strategies for employee engagement during the current Covid-19 pandemic and future virtual teams. Three future research propositions emerged from the literature review. This concept paper and associated research propositions will inform future employee engagement research on the impact of CCT on human interactions at work.
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Woods, M. (2021). Technology Impacts on Employee Engagement During Covid-19. In: Visvizi, A., Troisi, O., Saeedi, K. (eds) Research and Innovation Forum 2021. RIIFORUM 2021. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-84311-3_5
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COVID'19: A PANDEMIC-IMPACT ON EDUCATION SECTOR AND EMPLOYABILITY
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Consequences of COVID-19 on Employees in Remote Working: Challenges, Risks and Opportunities An Evidence-Based Literature Review
The COVID-19 pandemic forced organizations across all sectors and sizes to undertake crucial changes in order to remain productive during the emergency. Among these, the shift towards remote working arrangements is still present in our workplaces, impacting employees’ well-being and productivity. This systematic review aims to describe the pandemic’s consequences on work organization by analyzing whether and how the shift towards remote or home-working impacted employees’ productivity, performance, and well-being. Furthermore, it describes the role of individual and organizational factors in determining employees’ adjustment to remote work. Sixty-seven peer-reviewed papers published from 2020 to 2022, written in English, were selected through the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Findings describe how remote working arrangements, the workplace and organizational factors, and the employees’ individual traits and skills impacted employees’ productivity and well-being. Furthermore, they provide a description of the organizational enforcement actions reported in the literature. Managerial and practical implications, such as enforcement actions, team management strategies, and initiatives to promote employees’ physical and mental health, will be discussed in the paper.
1. Introduction
At the end of 2019, the coronavirus disease 2019 (COVID-19) became a pandemic: it began in Wuhan, China, but rapidly spread all over the world. On 30 January 2020, the World Health Organization (WHO) declared the outbreak of the COVID-19 pandemic as a public health emergency of international concern [ 1 ]. Considering the severe consequences of the COVID-19 pandemic on individuals’ physical health as well as on public health and social systems, governments adopted strict prevention measures. There were however differences between countries, also in relation to the different phases of the COVID-19 pandemic [ 2 ]. Some people could not go outside of their houses, while in other countries lockdowns did not last long and reached only specific economic sectors [ 3 ]. Among the most recurrent measures to contrast the COVID-19 pandemic was the mandatory closure of schools, the interruption of all nonessential productions and commercial activities, and the transformation of the workplace from a physical office space into a virtual place [ 4 ].
The national lockdowns that were implemented to stop the spread of the virus forced many organizations to turn suddenly into remote work, pushing towards a much greater use of technology [ 5 ]. At the same time, before the pandemic, most workers had little remote working experience, nor were they or their organizations prepared to support these practices [ 6 ].
The sudden spread of technology-based working arrangements resulted in a high number of international reports and scientific papers describing employees’ working conditions, using several different terms, such as remote working [ 7 , 8 ], teleworking [ 9 , 10 ], and working from home [ 11 , 12 ]. Despite the differences among them (for example, remote or teleworking not necessarily imply that the employee is working from home), it is not possible to universally define technology-based work arrangements [ 13 , 14 , 15 ]. For this reason, throughout this paper we will use remote working and teleworking as synonyms and will refer to work from home or home-working when the papers we are citing used such terms.
Apart from the issues linked to definitions of remote working, most organizations were not ready or willing to move in this direction. Nevertheless, the changes endorsed because of the pandemic generated a new workplace panorama. It is improbable that the previous organizational assets will be restored due to the substantial changes that the pandemic has somehow imposed and promoted. Current research and reports, indeed, suggest that remote working or, more generally, flexible forms of work will be implemented even after the pandemic’s end. In other words, different forms of hybrid work are becoming a stable feature of the workplace [ 16 , 17 ].
In this light, it is interesting to understand the challenges, opportunities, and risks related to remote working that impacted organizations during the COVID-19 onset and spread [ 18 ]. The organizational changes enforced now are the result of two processes. On one hand, they refer to organizations’ answers to an exceptional period, to find ways to survive or even grow. On the other, they are new forms of working that have proven to be effective in the short run but require attention regarding employees’ well-being and organizational productivity. It is then essential to understand which lessons are to be learned from remote work, which seems to be the most relevant change introduced in the workplace [ 9 ].
Of course, the different lockdowns or periods in which a number of restrictions were imposed were themselves a stressful event. However, the push towards remote work and, in general, towards new ways of working linked with information and communication technology (ICT) emerged during this phase and generated knowledge and experiences that need to be capitalized upon [ 19 ]. Therefore, this stage is highly needed: the phase of dramatic change may be over, but there are changes due to the widespread remote work that will still continue to have an impact.
Work organization has dramatically been re-arranged, following different schemes, depending on different dimensions: the availability of ICT and employees’ skills before the pandemic; the actual feasibility of this change according to the sector in which the organizations operate. For example, the remote working transition was possible mainly among office-based work but not among production plants or manufacturing sites [ 5 , 10 ]. Consistently, an ILO policy brief published in 2020 showed that only 20 to 34% of the workforce could work from home, based on the tasks and characteristics of different types of jobs [ 20 ].
The relative feasibility of the remote transition for office-based organizations implied that some organizations or employees moved from office-based work to full-time home-based work [ 21 , 22 , 23 ]. In some cases, employees were allowed to choose whether they wanted to work from home; in other instances, it was required either by national laws to counter the pandemic or it was mandatory as a result of organizational decisions [ 24 , 25 ]. Finally, there were different phases, where employees had to stay at home, while in other periods, employees could go back partially or totally to the office to work [ 26 ].
While in some cases the tasks involved in the remote working phase were just the same as the ones pursued before the pandemic onset, in most cases, new tasks were added due to the general changes faced by the organizations [ 27 , 28 ]. Furthermore, new strategies were implemented to introduce higher flexibility or innovation, for example, when establishing new forms of social support from colleagues or supervisors to overcome difficulties and problems arising from ICT use [ 27 , 28 ].
In any of these cases, remote or home-based work requires changes in the strategies implemented to monitor employees’ work and performance. Remote working makes it impossible to use well-known, office-based performance evaluation strategies [ 29 , 30 ].
Overall, studies and reports on the pandemic’s impact on organizations (across all sectors and sizes) highlight the profound changes that organizations were forced to undertake to remain productive during the different lockdowns [ 8 , 31 , 32 , 33 ]. As stated before, these changes still inform our workplaces. Thus, this review aims to describe the pandemic’s consequences on work organization by analyzing whether and how the shift towards remote or home-working impacted the employees’ productivity, performance, and well-being. Furthermore, even in consideration of the unexpectedness of the COVID-19-related events, this study describes the role of individual and organizational factors in determining employees’ adjustment to remote work.
The paper selection process followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement [ 34 ]. Eligibility criteria were empirical studies published in peer-reviewed full-length articles from 2020 to 2022, written in English. The period of literary research lasted from May 2020 to July 2022.
2.1. Information Sources and Search Strategy
Databases and search engines employed for the search were: EBSCOhost, ProQuest, and Web of Science. Each database required a different detailed strategy. At the same time, the following generic combination of keywords covered the focus of our research:
“Remote working” or “telework” or “eworking” or “e-working” or “work from home” or “home-based tele-work” or “virtual working” or “telecommuting” or “smart working” or “agile working” or “agile work” or “smart work” or “teleworking” or “ework” or “e-work” or “home working” or “home work” or “home-based work” or “home based work” or “home-based working” or “home based working” “home-working” or “home-work”
“Psychosocial risks” or “well-being” or “wellbeing” or “stress” or “technostress” or “tecnostress”
The keywords were searched in the publication title or abstract according to the needs.
2.2. Data Collection Process
All references were gathered in a Mendeley database. Two authors independently reviewed selected references, thus obtaining the final list of documents to be analyzed. As the chosen databases allowed to preselect full-text availability, year, and language of publication, this manual selection procedure mainly regarded paper content. Papers in which the content was not entirely within the scope of this review (e.g., theoretical position paper, prescriptive approaches, best practices) and did not include empirical research were eliminated. Furthermore, the authors scrutinized the reference section of selected papers, looking for further works written in English that could fit the eligibility criteria. They also read their abstracts to check whether they could be included in the review.
Figure 1 [ 35 ] shows the whole workflow that brought about the final paper selection.
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is ijerph-19-11672-g001.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9517495/bin/ijerph-19-11672-g001.jpg)
Study selection workflow.
2.3. Study Selection
After applying the inclusive and exclusive criteria ( Figure 1 ), 67 papers were determined as eligible and were included in the review (included papers are marked with an asterisk in the references list).
Seven main themes emerged from the content analysis of the papers. Figure 2 shows how the papers are distributed across the categories. As shown, almost all the papers (N = 64) refer to employee well-being conditions, whether impacted by the workplace, the individual or the organizational factors. A total of 37 papers, instead, described the impact of remote working experiences and conditions on productivity and performance. Furthermore, Figure 2 indicates how many papers include contents specifically related to one category among the ones individuated (Papers exclusively in this category in Figure 2 ). With this regard, it is interesting to observe that several papers focus on one category (N of papers addressing only one category = 43), with categories on the impact on employee well-being being the most represented across the papers.
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is ijerph-19-11672-g002.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9517495/bin/ijerph-19-11672-g002.jpg)
Papers distribution across categories.
3.1. Impact of Remote Work on Individual Performance and Productivity
Several research contributions among the ones selected for this review describe the effects of remote or home-working on employee productivity.
Before considering the effects of such working arrangements on performance and productivity, a first reflection on the performance assessments has to be done. From the paper analysis, it emerges that the assessment by employees of their quality of work and productivity is not the same across different professional groups. For example, in a study in Italy, teachers reported a lower perceived quality of work than other professionals [ 36 ]. On the other hand, when the job tasks are usually pursued in an office, the work-from-home arrangement seems to boost the perceived performance [ 36 ]. These differences likely depend on the tasks usually performed at work and the ICT literacy of the employees. In the case of teachers, despite having potential good ICT skills because of the use of technology in the classroom, videoconferencing tools to interact with students may have negatively impacted the quality of their work.
Concerning the effects of remote working on employees, many selected papers describe issues related to stress and anxiety conditions, mainly due to the consequences of full or partial national lockdowns that forced remote or home-work, or the fast switch to the use of ICT. Overall, such conditions affected employees’ well-being and, in turn, their productivity [ 19 , 37 ].
At the same time, some studies showed that when employees were satisfied with their telework conditions, they experienced higher subjective well-being and better self-reported performance [ 38 ]. Further, subjective well-being emerged also to partially mediate the relationship between telework satisfaction and self-reported performance [ 38 ].
Interestingly, in a study performed among a group of employees working from home in Hong Kong, stress did not directly impact productivity but promoted non-work-related activities during working hours, such as caring for children, doing housework, or playing video games and sports. However, performing these non-work-related activities did not affect productivity, suggesting that this may effectively counteract stress [ 39 ].
In this regard, the participants of a Czech study reported that they found their work from home more efficient than in the office. Moreover most of the 90 employees interviewed showed a positive perception of home office employees with regards to saving time, or the feeling of freedom, while confirming the adverse effects of isolation [ 40 ].
These findings are interesting since they show that remote work per se does not bring positive or negative outcomes, but rather that the consequences depend on many individual and work factors. Therefore, the following sections will describe individual and organizational factors that contribute to shaping the effect of remote working on employee performance during the pandemic.
3.2. Impact of Individual Factors on Individual Performance and Productivity
In line with the previous literature on job satisfaction, employees’ satisfaction with remote work has also emerged as being strongly linked with productivity [ 41 , 42 ].
For instance, employees satisfied with the ICT tools at work are more willing to explore additional features of their systems while also seeking more effective ways to execute their work tasks, thus enhancing their performance and innovativeness [ 19 , 43 ].
In the same line, a longitudinal study carried out in Colombia on employees who compulsorily switched to teleworking because of the pandemic showed that work–home conflict and work overload generated strain, which decreased job satisfaction with telework, and thus perceived job performance [ 44 ].
Concerns about contracting the virus have also proven to play a role in productivity: remote work satisfaction in an Italian group of employees was higher for employees with higher perceived productivity and lower concern about the virus [ 42 ]. In other words, the relationship between work satisfaction and perceived productivity is moderated by concern about the virus [ 42 ]. Not surprisingly, satisfaction with COVID-19 countermeasures among employees working in the office, and thus with employees’ perceived safety, was significantly associated with work productivity [ 45 ].
Regarding individual performance, in a study carried out among academic staff in Indonesia, it emerged that digital orientation (i.e., an individual’s commitment towards the application of digital technology to support the accomplishment of the job) impacts employees’ digital capability, which in turn affects their productivity. In other words, digital capability mediates the relationship between digital orientation and productivity [ 12 ]. Consistently, a study on software engineers showed low to no suffering due to the home-working condition, thanks to the high familiarity with ICT tools that allowed them to create the best possible conditions at home to pursue their goals [ 46 ].
Another factor affecting performance is procrastination, which exerts a highly detrimental impact on individuals’ work effectiveness from home [ 8 ]. Indeed procrastination emerged as a problem with productivity at work when not counterbalanced with self-discipline [ 8 , 40 ].
Finally, it emerged also that work-home interference plays a detrimental role in performance. From the interviews collected in the study, it emerged that working parents faced a more significant challenge in balancing work and family duties, especially when working at home and at the same time having to take care of children who were out of school because of the lockdowns. More than that, more working hours were required very often. These interferences between work and family domains could make people feel exhausted and, therefore, less productive [ 8 , 40 ].
3.3. Impact of Organizational and Workplace Factors on Individual Performance and Productivity
Generally speaking, the organizational contexts supporting mental, physical, and social functioning have increased employee productivity during the pandemic. In addition, some papers focused on enforcement actions that positively affected employees’ productivity and job satisfaction [ 37 , 47 , 48 , 49 , 50 , 51 ].
The pandemic induced occupational discomfort, namely the lack of proper telework conditions from home, which impacted job performance. Occupational discomfort refers to the lack of clear policy about working from home, experiencing poor ICT connectivity, inadequate personal space, time management, limited guidance, poor ergonomic premises, and no peer communication [ 41 , 48 ]. Furthermore, all types of multitasking and interruptions from colleagues, supervisors, and their family members, were mentioned as detrimental to employee productivity. It is interesting to note that women are more exposed to these latter problems [ 52 ].
Not surprisingly, productivity was enhanced among organizations that provided resources to create a proper work environment at home as well as technical assistance and specific training for the new ways of working [ 37 , 48 , 49 , 50 ].
Leadership, of course, plays a relevant role in determining employees’ productivity.
Leaders promoting a sustainable way of working for their employees boosted their organizational commitment and extra-role behavior, which, in turn, are antecedents of higher productivity [ 5 ]. Sustainable leadership refers mainly to the ability to offer guidance and avoid intrusive monitoring [ 8 , 47 ]. Positive and effective leadership behavior examples included the ability to acknowledge the quality and quantity of the work done by employees, despite not having the chance to monitor them directly, and, consequently, assigning the right amount of work to prevent workload [ 7 , 10 , 26 , 36 , 53 , 54 , 55 , 56 , 57 ].
Another valuable leadership skill reported in the papers includes monitoring and promoting social support, especially in sharing digital support among employees [ 58 ]. Thanks to these initiatives, employees are helped to overcome reluctance and apprehensiveness related to the use of ICT and their dependency [ 59 ]. A further issue tackled by positive and effective leadership leading to productivity is the handling of teams. Introducing new norms and standards about online communication and asynchronous collaboration could overcome conflicts among team members related to delays, interruptions, different individual work rates, or workloads not distributed equally. These problems were a serious menace to team performance and productivity [ 47 ].
Finally, communication is another organizational factor linked to performance. A study in China showed that ineffective organizational communication negatively impacted individuals’ work effectiveness from home [ 8 ], specifically when employees did not receive the necessary instructions and information to perform their duties.
3.4. Impact of the Workplace on Well-Being
Several studies highlight how productivity in the workplace is strongly linked with employees’ physical and mental well-being [ 39 , 45 , 50 , 60 ]. The pandemic changed the workers’ routines and lifestyle, generating problems both in physical and mental/psychological health [ 24 ].
Regarding physical distress/problems among workers during the lockdowns, several studies report confinement to home and sedentary activity leading to the discomfort of different body parts [ 61 ]. Musculoskeletal pain emerged as a consequence of the imposed sedentarism and the inadequacy of the physical premises available at home, such as lack of ergonomic chairs, proper lights, or a private space to work [ 11 ]. In addition, new ways of working were introduced in most cases very rapidly, without the opportunity to organize and revise them to prevent distress both at physical and psychological levels [ 62 ].
These sudden changes affected working routines and habits. For example, a study in Japan reported that employees who worked remotely instead of in the office because of the pandemic spent less time doing physical exercises compared to colleagues who already worked remotely before the COVID-19 restrictions and those who worked from the office [ 63 ]. This finding is in line with the worsening of sleep quality, decrease in work-related health, and decline in physical functioning found in other studies [ 64 ]. Consistently, a study in Canada flags screen fatigue problems [ 65 ] due to longer work hours while working from home than in the office.
In many cases, the new way of remote work affected the quality of working life due to the difficulties in disconnecting from work, thus working longer hours.
A number of factors related to organizational factors also affected the psychological well-being of employees. For example, a study developed in Romania has shown a positive relationship between remote working and perceived professional development levels, job satisfaction, and well-being [ 66 ].
At the same time, several organizational factors affected employees’ well-being, generating depression, anxiety, and stress among employees [ 19 ]. These factors include: working extra hours, having a heavier workload, feeling socially isolated, worsening feelings of job security, experiencing difficulties in accessing the necessary work tools from home [ 67 ], and feeling a strong demand for new ICT-related skills to cope with the new ways of working. However, it is important to first acknowledge the role of the pandemic itself and the fear of contracting the virus. A study differentiated between the sources of ill-being, showing that a significant part of the anxious and depressive symptoms was due to COVID-19-related conditions instead of work arrangements [ 37 ].
Furthermore, factors such as longer working hours and the general home-working arrangement impacted employees’ well-being even in other forms, for example, by compromising work-life balance or reducing the time devoted to leisure, family duties, and friends [ 68 ].
The pandemic-related arrangements impacted the quality of work life as well. Isolation made it more challenging to receive and ask for help from colleagues and reduced the quality of interpersonal exchange; isolation also meant problems connected with poor or difficult communication due to the sudden changes in the organization of work [ 8 ]. Isolation also undermined the sense of belonging to the organization, which, in turn, caused depressive symptoms [ 69 ]. Following this line of thinking, a study carried out among administrative and teaching staff of Iraqi universities found that telework only reduces job stress when employees do not believe it will lead to social isolation [ 70 ].
Job demands for new ICT skills and procedures elicited a sense of professional inadequacy among employees, as well as the fear of losing their job and facing financial instability. The latter was also connected to the financial difficulties faced by the organization or the automation of certain job tasks, or the competition with colleagues having higher ICT skills [ 7 ]. Several studies refer specifically to techno-stressors, that is, stress factors linked directly to the use of ICT. These include techno-overload, related to the intensification and increased workload connected with the introduction of ICT, and techno-invasion, related to the blurring of boundaries between work and private contexts due to ICT use (see i.e., [ 16 , 28 , 65 , 71 ]). Some papers refer to work overload, which is the perception of having too many work-role tasks to fulfill, due to the new way of working and not having enough time to do them, despite the time saved for commuting or going to the office [ 52 ]. Linked with it is also reported a required high level of multitasking, as well as work-based interruptions (such as these linked to family tasks), generating lower performance [ 52 ].
3.5. Impact of Individual Factors on Well-Being
It has to be noted that these factors did not emerge as affecting all workers in the same way. In fact, some groups of workers were more affected than others.
Some studies analyzed the role of gender in the risk for employees’ physical and mental health problems. For example, in a study carried out in India, it emerged that women were more affected by organizational and social stress [ 72 ]. Moreover, in a study carried out in Egypt among university staff members, high levels of technostress were linked with the female gender and a lousy workplace environment [ 73 ]. Studies comparing women and men show quite a consistent pattern, where women report more stress and more difficulties, worsened by a bad workplace environment [ 26 , 52 , 66 , 72 , 73 , 74 , 75 ] as well as a higher number of hours devoted to child care and home tasks [ 72 ] in comparison with men. Similarly, a Canadian study showed that marginalized workers (women, migrants, and people facing financial hardships) reported lower job security, which was related to lower well-being scores [ 76 ].
Even other demographic factors impacted the quality of work and life during the pandemic. For example, a study carried out in Germany and Switzerland reported that younger age, living alone, reduction of leisure time, and changes in the quantity of time devoted to caring duties were associated with more detrimental psychological outcomes on personal life. On the other hand, living with a partner or family, short-time work, increase in leisure time, and caring duties were associated with positive mental well-being [ 18 ].
Social conditions were reported as well. For instance, among a group of school teachers in Chile, more than half suffered from poor mental health, but those more prone to psychological problems were working in private-subsidized schools, working overtime hours [ 77 ].
In line with previous literature on stress, a couple of studies addressed the relevance of employees’ activation of proactive coping strategies, such as help-seeking and active problem-focused coping, recreation, and relaxation activities to cope with work-related stress [ 57 , 78 ].
Employees’ cognitive appraisal of their work is also linked to individual well-being: in the case of telework, a study developed in Romania reported a positive relationship between professional development and competencies, job satisfaction, and well-being, and a negative relationship between the emotional dimension, commitment, autonomy, and well-being [ 66 ].
Other studies dealt with dispositional traits related to individual well-being. For example, from a study carried out among a group of employees working from home, it emerged that those with a “solitary profile” (i.e., high levels of preference for solitude and neuroticism, low levels of extraversion and agreeableness, and moderate levels of conscientiousness and openness) reported higher loneliness at work, higher levels of stress, and lower levels of job satisfaction and work engagement than those with an “affiliative” profile (i.e., low levels of preference for solitude and neuroticism, high levels of extraversion and agreeableness, and moderate levels of conscientiousness and openness) [ 79 ].
Another powerful personal resource affecting individual well-being is self-discipline. Workers who considered themselves self-disciplined claimed to be more able to deal positively with the work-family balance, than those who described themselves as less self-disciplined, completing their work more efficiently and timely [ 8 , 80 ].
Self-compassion also emerged as a competence able to promote employees’ well-being: workers with a higher score in self-compassion show lower levels of depression and loneliness. This association is because self-compassionate employees are more likely to feel connected with others during the challenging experience of work loneliness imposed by the lockdowns. Moreover, they also tend to be more aware of and more ready to accept their feeling of loneliness [ 69 ].
In line with this, mindfulness turned out to be positively related to job satisfaction and negatively associated with technostress [ 19 , 41 ]. Although mindful employees are more likely to assess their working conditions, they are more able to respond more objectively to the demands and challenges posed by the new situations, thus lowering the impact of techno stressors and feeling more competent about them their professional skills [ 19 ].
Similarly, emotional intelligence has also been shown to reduce the negative impact of social isolation on employees’ well-being [ 81 ]: in fact, people who hold a higher level of emotional intelligence are more able to perceive, empathize and regulate their emotions, thus becoming more able to develop stronger and more positive relationships with others which, in turn, promotes their well-being [ 81 ].
3.6. Impact of Organizational Factors on Well-Being
The pandemic has had different effects on employees’ personal lives according to the extent to which it generated dramatic changes and, more than that, on the degree to which employees experienced an opportunity to influence their work and life. How organizations changed and managed employees’ work during the pandemic has proven to impact employees’ well-being [ 76 ]. In this line, perceived autonomy and job crafting correlate negatively with stress and positively with workload [ 82 ], showing that workers who feel unable to contribute constructively to their job are more prone to psychological distress [ 83 ].
Job crafting is crucial when used to grow flexibility and spend more time with family. In these cases, employees show a higher level of psychological health than those who struggle to balance their private life with their working life due to the interference between home and work during remote work and an increase in daily working hours [ 52 ]. Consistently, work hours can extend easily when the employees work at home. Hence, leading to an increase in daily working hours [ 84 ]. This factor is often combined with another work stressor: role overload. Role overload refers to the extension of the duties and tasks required when the employees work from home, and it was reported to be especially frequent during the pandemic [ 41 , 52 , 67 ].
Another valuable dimension is job autonomy. Job autonomy, indeed, is negatively correlated to loneliness, suggesting that employees who are, to some extent, free to organize their workday feel a higher sense of connection and relatedness than those who are subjected to different ways of working [ 8 ]. On the other hand, in a study carried out in Japan, it emerged that those who were forced to move from office work to telework were less satisfied than those who continued working from home, independently from the outbreak [ 63 ].
Job autonomy also refers to employees being able to take care of their mental well-being and alleviate the perception of cognitive overload by implementing “digital detox measures”. Employees applied limits on their use of technologies, for example, switching off notifications, powering off electronic devices at a specific time in the evening, or responding to emails only at a predefined time [ 85 ].
Interestingly, autonomy in another study emerged as being correlated negatively with employees’ well-being in the case of telework [ 66 ]. Unfortunately, the studies mentioned above do not report on the extent of the autonomy granted to the employees. However, this factor might be related to another factor: the role played by the leadership. The degree of monitoring procedures implemented by leaders, indeed, may undermine a positive work-life balance [ 86 ] by impacting employees’ stress and well-being, mainly when performed in an intrusive [ 8 ] or authoritative [ 7 ] way. Moreover, quality leadership has proven to contrast counterproductive work behaviors and promote organizational citizenship behaviors through internal marketing [ 51 ]. At the same time, a lack of “ COVID-19-related informational justice” by the management led to depressive symptoms [ 69 ].
On the contrary, positive and effective leadership impacts employees’ well-being [ 26 ], contrasting and preventing stress. At the same time, when leaders can promote and sustain organizational and social support, they increase the perception of psychological safety [ 8 , 32 ]. Employees who feel their organization is taking care of them and their work develop positive emotional resources. In these cases, a present and caring leadership style represents a form of adequate organizational support [ 41 ].
Moreover, coworkers’ support is linked to a lower workload perception and a more positive work-home balance [ 8 ]. Finally, social support elicits emotional resources, making employees more able to cope with the challenges and demands of work [ 32 ].
Quality in interpersonal relationships among colleagues and managers has also proven to bring other positive effects. For example, a study carried out in Poland involving 220 IT employees showed that good employee relationships can have a positive effect on job satisfaction. Also, interpersonal trust in managers mediates the relationship between employee relations and job satisfaction [ 53 ]. Consistently, another study showed that quality interpersonal relationships with colleagues boost positive coping strategies (i.e., help-seeking and active coping), which promote well-being and quality of work life [ 57 ].
In terms of more general management, a study showed the relevance of organizational communication. This factor indeed emerged to be positively associated with employees’ self-efficacy and negatively with technostress and psycho-physical disorders [ 87 ]. Furthermore, good organizational communication has also proven to prevent and contrast the feeling of being neglected by the employees, since their commitment to work may be questioned because they are not physically present. Recognizing the work done, in turn, contrasts occupational stress and is linked with employees’ loyalty [ 88 ].
4. Discussion
This literature review aims to systematize the substantial body of research focusing on the impact of the COVID-19 pandemic on remote working arrangements.
Due to the limitations imposed by the pandemic, workers suddenly switched from working in an office to remote or home-working. Overall, the studies analyzed show heterogeneous consequences on employees’ well-being, productivity and performance. Interestingly, in addition to papers that explored the positive or negative effects of remote working on well-being, productivity or performance [ 36 , 39 , 40 , 61 , 63 , 64 , 65 ], other categories of studies have also emerged [ 42 , 57 , 68 , 78 ]. These examined how employees’ characteristics shape their remote working experiences, thus influencing their productivity, performance, and well-being. In other words, how individual factors such as personal living conditions (e.g., the management of domestic spaces) [ 40 ], personal resources (e.g., coping strategies) [ 57 , 78 ], and perception of ability with ICT [ 46 ] influenced their evaluations of remote work. Similarly, organizational factors such as leadership style [ 5 , 7 , 47 ], co-workers’ support [ 8 ], and job autonomy [ 8 , 66 ] have also positively or negatively influenced employees’ perceptions about the transition and implementation of remote work. From this, it can be concluded that remote or home-working is not intrinsically fruitful or harmful, but that personal or organizational factors have characterized its perception. Consequently, during the lockdown periods, remote working represented an opportunity for some employees to increase their quality of life [ 66 , 76 , 83 ] and a source of personal or work distress for others [ 8 , 51 , 63 ]. While organizations cannot intervene on personal dispositions towards stress sensitivity, these data are helpful, as they underline which dimensions can be linked to a higher risk while teleworking and which can lead to a higher adaptation and well-being. The organizational factors promoting or mining a fruitful use of remote working can be reorganized and strategically planned to reduce employees’ risks and improve their productivity, performance, or well-being.
An interesting reflection concerns the role of technologies and their perception by employees.
It must be noted that the shift towards remote work through ICT has mainly been addressed during the pandemic as a necessary but also challenging choice for helping firms’ financial and operational sustainability [ 5 ]. On the other hand, the impact of a rapid and sudden introduction of ICT in the workplace has often been perceived (and addressed) in relation to the negative consequences of reduced interpersonal interaction among members of the same organization [ 8 ]. In this respect, in fact, such an innovation has been often perceived as a serious risk of stress and burnout [ 19 , 37 ]. In reality, the use of technology in most cases was almost the only way to preserve interaction and interpersonal relationships among workers during the lockdowns [ 27 , 28 ]. ICT can also be addressed as a new, different way of interacting among workers, thus presenting not only difficulties but also points of strength [ 89 , 90 ]. The condition under which ICT may jeopardize or promote social support is an aspect that would deserve to be further explored in the future.
On the other hand, a factor that was little explored but could have had a combined effect with work-related stress was the concern for COVID-19 experienced by employees. Fear of getting infected likely made employees feel insecure about their health and safety [ 91 ].
Toscano and Zappalà [ 42 ] showed a relationship between stress, perceived productivity, remote job satisfaction, and concern for COVID-19. Building on this, it is likely that this aspect influenced findings from other studies not addressing the COVID-19 concerns. Consequently, it would have been helpful to investigate to what extent the pandemic threatened employee productivity and well-being and to verify the specific role of remote work arrangements on the same outcomes. In the other words, it may be useful to distinguish between different factors: the stress generated by the workers’ fear of deteriorating their financial condition in relation to the consequences of the pandemic [ 7 ], the concern for their health due to the spread of the COVID-19 [ 91 ], the difficulties in dealing with a new way of working (namely, using ICT) [ 7 ], as well as the new ways of interacting with other members of the same organization [ 89 ].
Future studies on remote working arrangements in different phases of the pandemic management may help figure out how remote conditions themselves impact employees’ experiences of work and its integration with private life.
A further interesting line of study is the role played by interpersonal trust in promoting employees’ well-being and mental health [ 53 , 57 ]). Indeed, as shown in previous studies, interpersonal trust in the workplace has emerged as a strong protective factor after another catastrophic financial event which was the 2008 worldwide financial and economic crisis [ 92 , 93 , 94 ].
Finally, to the best of our knowledge, only two longitudinal studies [ 44 , 95 ] have been conducted about the effects of remote working on productivity and well-being. Further studies may help to understand the pandemic’s extended consequences and the remote working arrangements, likely allowing to model the specific effects of each condition.
Next to the mentioned detrimental effects, several studies showed how the pandemic led to an unexpected and forced organizational change that created multifaceted conditions of performance, productivity and well-being related to remote working [ 5 ]. Even involuntary and unplanned changes imply organizational structure or process transformations [ 96 ]. They can be addressed through a cycle of structured actions, including establishing a sense of urgency, forming a powerful leading coalition, creating and communicating a vision, enabling others to act on the vision, planning and creating short-term victories, consolidating improvements to bringing about more change, and institutionalizing new approaches [ 97 ]. These models highlight that a deep understanding of employee attitudes and behaviors towards such changes is essential to address them successfully and minimize negative consequences [ 98 ]. On the contrary, if this condition is not satisfied, employees may show adverse reactions, such as resistance, resentment, and disengagement, that can inhibit the successful implementation of organizational change [ 99 ].
A general consideration must be made about the type of remote working conditions studied during the pandemic. COVID-19-related remote working conditions, indeed, required a peculiar form of adaptation and adjustment for several reasons [ 48 ]. Firstly, remote working before the pandemic represented an alternative to office work offered to employees to promote a higher work-life integration [ 100 ]. During the pandemic, instead, it became a full-time mandatory practice, thus losing the voluntary nature that characterized it [ 48 ]. Secondly, remote working was considered the only tool to ensure corporate continuity during the crisis. However, several organizations were not ready (from a strategic, instrumental, and technological point of view) to implement this new arrangement [ 6 ]. In this regard, the organizations that showed valuable abilities to manage the change process related to the pandemic were even able to reduce the impact of potential stressors on the employees by driving them in the change and implementing practical actions to support their well-being, performance, and productivity [ 49 , 50 ].
5. Conclusions
It is unknown what will be left of remote work and in which organizational contexts it will persist since many national contexts are still elaborating laws and regulations to define the administrative boundaries of such practices [ 101 , 102 ].
Indeed, the COVID-19 pandemic and the following organizational changes brought positive consequences. Organizations, especially leaders, confirmed that many good practices concerning increasing ad hoc skills in managing remote work and strategies and positive habits promoting psychological and physical well-being could be implemented. In this regard, the review’s collected studies have shown a wide range of mental and physical health promotion programs, new approaches to online training, and creative ways of socializing at a distance. These strategies have been shown to effectively alleviate potential work stressors and improve the workers’ adjustment to remote work [ 27 , 37 , 49 , 50 , 103 ]. At the same time, virtual learning and development, communication exercises, live sessions for training new skills, digital classroom training modules, e-learning modules, and many other creative learning sessions have been the starting point to sustain teleworkers’ performance during the COVID-19 pandemic [ 49 ]. Moreover, such programs were often paired with technical and ergonomic resource provision, even through technical assistance and specific trainings [ 37 , 48 , 49 , 50 ]. These practical forms of support boosted other forms of organizational communications around the vision of change and rewarding procedures involving employees [ 51 ]. Overall, the studies showed that organizations that provided both instrumental and relational support have effectively managed organizational change and allowed the employees to adjust to remote work.
The enforcement actions developed during the pandemic will be described in more detail in the following section dealing with managerial implications. In fact, they can also represent useful intervention methods in the future context of hybrid work.
5.1. Managerial Implications
Organizational factors that promote or hinder an effective use of remote working can be strategically reorganized and planned to improve employees’ productivity and well-being. Our results highlight which dimensions can be considered obstacles in the remote or home-working practice and which ones can lead to a greater adaptation and well-being.
Several studies showed how some organizations endorsed positive actions with COVID-19-related work issues and supported employees’ well-being and productivity.
During the pandemic, organizations supported employees’ social well-being by implementing engagement actions and promoting a culture of trust and collaboration, thus promoting their social well-being [ 37 , 47 , 49 , 50 , 53 ].
Most of these programs have focused on promoting employees’ mental and social well-being [ 27 , 37 , 49 , 50 , 53 , 103 ].
Some organizations have introduced webinars focusing on anxiety and stress, online meditation classes, and training to develop new daily habits about health, hygiene, and the positive work-life balance of employees [ 49 ]. Other organizations have also provided access to yoga and fitness instructors to compensate for sedentary lifestyles and lack of physical activity in teleworkers, which, together with harmful eating habits, can lead to severe issues (such as obesity, cardiovascular disease, diabetes mellitus) [ 50 ].
Some activities aimed to empower workers, increase awareness of the current situation, and analyze the pros and cons of remote/home-working [ 37 , 49 ]. In the academic context, the researchers were involved in virtual empowering sessions on different topics, such as individual differences in addressing the COVID-19 challenges, managing the crisis, and how to thrive during and not just survive [ 37 ].
Other developed actions to motivate the teams have been weekly alignment sessions, team meet-ups, virtual challenges and competitions, online courses, sharing content such as TED Talks or online books, webinars with industry experts, and online counseling sessions. Organizational support was also expressed through “family engagement practices” as intended online babysitting, in which employee kids were kept engaged for a few hours while parents worked from home [ 49 ]. At the same time, other practices had a more informal and playful character [ 50 ]. For example, in some organizations, the leaders organized team-building activities and virtual events such as lunch in a video conference [ 49 ], online happy hour, hidden talent show, virtual karaoke, and campfire challenges [ 50 ].
Each of these actions helped develop a positive relationship between superiors and employees so that these last members felt free to discuss any issues and concerns [ 50 ].
More frequently, team leaders had more individual online meetings with other members to check their mental health and assess the team’s mood [ 53 ]. Teams have also independently developed peer support actions [ 21 , 47 ].
Employees established fifteen-minute “online morning huddles”. The purpose of these informal meetings was to take care of others and check their well-being through questions that concerned not the work but the personal sphere of colleagues (e.g., family). In addition to stemming the sense of loneliness, this good practice has helped develop a compassionate culture among members and created cohesion [ 21 ].
These listed are examples of good practices that have had a positive impact on employees working outside the workplace during the pandemic. These executive actions, developed in a pandemic context, could continue to be used even in the context of normal life or still characterized by restrictions representing precious approaches to intervention for promoting employees’ productivity and well-being in a sort of “heterogeneity of purposes” [ 104 ].
5.2. Practical Implications
A section of this paper deals with effective ways and interventions to address stress and challenges posed by the COVID-19 pandemic, in the hope that such information will constitute a resource for managers and HR consultants.
5.3. Challenges, Risks and Opportunities
The main challenge will be to adapt these new ways of working in a post-pandemic situation. This process could include various factors, such as the type of organization, the size of the organization, the organizational culture, and the implicit norms already present within each organizational reality. Furthermore, leaders could model the perception of ICT use, helping employees to perceive technology as a means of facilitating the performance of tasks and professional and social interactions.
However, as highlighted by some studies in this review, the main risk is to organize flexible work arrangements forgetting their initial assumptions instead of increasing the employees’ autonomy and flexibility and improving their work-life integration.
Regarding the opportunities, organizations could further apply the enforcement actions developed during the pandemic. These good practices can have positive effects on employees’ well-being and productivity also in a post-pandemic work environment.
Furthermore, the consistent post-pandemic use of flexible work arrangements can promote research on the impact of technology-mediated strategies promoting employees’ flexibility and autonomy on their well-being and productivity. In this regard, longitudinal research designs could be used to have a better picture of the phenomenon.
5.4. Limitations and Strengths
Our study took into consideration peer-reviewed papers, published in English in international journals. We realized, though, that there is much more material published in other languages, which might have offered interesting insights. Moreover, other papers about the pandemic’s consequences on the workplace and employees’ well-being may be published soon. On the other hand, it was important to start a reflection based on the studies already carried out and deepen the knowledge about this topic.
This is exactly the main strength of this paper. Having a detailed view of workplace changes and valuable indicators such as employees’ performance, productivity and well-being can enable future work organization development and how to deal with new challenges.
Funding Statement
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Conflicts of interest.
The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Sustainable strategies for innovative cooperation in human resources training between the business sector and universities through internship programs from the pre- to post-covid-19 period.
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1. Introduction
2. literature review, 2.1. internship, 2.2. human resources training and development, 3. materials and methods, 3.1. participants, 3.2. instruments.
- The first section has two questions and concerns the information on personal data and the consent/assent of the research participant (question 1, open-ended, and 2, closed-ended).
- The second section has 8 questions and is about the demographic characteristics of the beneficiaries and the characteristics of the internship they implemented (questions from 3 to 10 are closed-ended except the 8th one which is open-ended), related to gender, age, the year of study they belonged to when they implemented the internship, the department of study, the academic year in which the internship was implemented, the name of the host organization, the duration of the internship, and finally a question about their continued employment at the host organization after the end of the internship.
- Learning Outcomes, 17 questions
- Efficiency, 7 questions
- Emotional Commitment, 6 questions
- Satisfaction, 8 questions
- Participation, 6 questions
- Empowerment, 5 questions
- Role Ambiguity, 3 questions
- Role Conflict, 3 questions
- Supervisor, 3 questions
- Cooperation, 2 questions
3.3. Procedures
3.4. data analysis.
- learning outcomes and satisfaction with a correlation coefficient of 0.808 **.
- learning outcomes and efficiency with a correlation coefficient of 0.774 **.
- efficiency and satisfaction with a correlation coefficient of 0.702 **.
- participation factor and supervisor (0.357 **).
- participation factor and cooperation (0.336 **).
- participation factor and learning outcomes (0.520 **).
- participation factor and role ambiguity (0.382 **).
- participation factor and satisfaction (0.448 **).
- participation factor and efficiency (0.535 **).
- supervisor factor and cooperation (0.449 **).
- supervisor factor and learning outcomes (0.564 **).
- supervisor factor and role ambiguity (0.495 **).
- supervisor factor and satisfaction (0.552 **).
- supervisor factor and efficiency (0.526 **).
- cooperation and learning outcomes (0.446 **).
- cooperation and role ambiguity (0.424 **).
- cooperation and satisfaction (0.437 **).
- cooperation and efficiency (0.433 **).
- learning outcomes and role ambiguity (0.627 **).
- learning outcomes and emotional commitment (0.571 **).
- role ambiguity and satisfaction (0.628 **).
- role ambiguity and emotional commitment (0.347 **).
- role ambiguity and efficiency (0.570 **).
- satisfaction and emotional commitment (0.542 **).
- emotional commitment and efficiency (0.531 **).
- participation factor and empowerment (0.112 **).
- participation factor and role conflict (−0.114 **).
- participation factor and emotional commitment (0.288 **).
- supervisor factor and empowerment (0.150 **).
- supervisor factor and role conflict (−0.207 **).
- supervisor factor and emotional commitment (0.298 **).
- cooperation and empowerment (0.132 **).
- cooperation and role conflict (−0.109 **).
- cooperation and emotional commitment (0.254 **).
- empowerment and learning outcomes (0.168 **).
- empowerment and role ambiguity (0.104 **).
- empowerment and satisfaction (0.158 **).
- empowerment and emotional commitment (0.149 **).
- empowerment and efficiency (0.175 **).
- learning outcomes and role conflict (−0.127 **).
- role ambiguity and role conflict (−0.251 **).
- role conflict and satisfaction (−0.277 **).
- role conflict and emotional commitment (−0.081 **).
- role conflict and efficiency (−0.125 **).
- Participation F (2,1366) = 59.155, p < 0.05
- Supervisor F (2,1375) = 59.291, p < 0.05
- Cooperation F (2,1366) = 48.876, p < 0.05
- Empowerment F (2,1368) = 17.564, p < 0.05
- Learning Outcomes F (2,1350) = 64.179, p < 0.05
- Role Ambiguity F (2,1372) = 25.762, p < 0.05
- Role Conflict F (2,1374) = 6.611, p < 0.05
- Satisfaction F (2,1365) = 27.583, p < 0.05
- Emotional Commitment F (2,1361) = 6.772, p < 0.05 και
- Efficiency F (2,1357) = 75.040, p < 0.05
- For the Participation factor between the 2nd and 3rd levels.
- For the Supervisor factor between the 2nd and 3rd levels.
- For the Enhance factor between 2nd and 3rd levels.
- For the Learning Outcomes factor between the 2nd and 3rd levels.
- For the factor Role Ambiguity between the 2nd and 3rd levels.
- For the Role Conflict factor between the 1st and 3rd levels.
- For the Satisfaction factor between the 2nd and 3rd levels.
- For the Emotional Commitment factor between the 2nd and 3rd levels.
- For the Efficiency factor between the 2nd and 3rd levels.
5. Discussion
6. conclusions, 7. implications, 7.1. theoretical implications, 7.2. practical implications, 8. limitations and future research, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.
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Click here to enlarge figure
Frequency | Percentage | ||
---|---|---|---|
Duration | 1 month | 286 | 20.5 |
2 months | 885 | 63.3 | |
3 months | 227 | 16.2 | |
Total | 1398 | 100.0 |
Frequency | Percentage | Valid Percentage | ||
---|---|---|---|---|
Temporal areas | Era 1 | 463 | 33.1 | 33.6 |
Era 2 | 410 | 29.3 | 29.7 | |
Era 3 | 506 | 36.2 | 36.7 | |
Total | 1379 | 98.6 | 100.0 | |
Missing values | 20 | 1.4 | ||
Total | 1398 | 100.0 |
FACTORS | No. of Items | Loadings | Eigenvalue | Variance % | α | Factor Mean | Factor St. D. |
---|---|---|---|---|---|---|---|
Learning Outcomes | 17 | 0.739 | 12.430 | 20.717 | 0.963 | 3.699 | 0.929 |
0.729 | |||||||
0.810 | |||||||
0.744 | |||||||
0.784 | |||||||
0.772 | |||||||
0.715 | |||||||
0.670 | |||||||
0.649 | |||||||
0.611 | |||||||
0.598 | |||||||
0.528 | |||||||
0.719 | |||||||
0.689 | |||||||
0.658 | |||||||
0.692 | |||||||
0.559 | |||||||
Efficiency | 7 | 0.609 | 5.146 | 8.577 | 0.936 | 3.672 | 0.952 |
0.688 | |||||||
0.683 | |||||||
0.640 | |||||||
0.705 | |||||||
0.662 | |||||||
0.510 | |||||||
Emotional Commitment | 6 | 0.776 | 4.579 | 7.631 | 0.944 | 3.783 | 1.068 |
0.796 | |||||||
0.770 | |||||||
0.877 | |||||||
0.883 | |||||||
0.760 | |||||||
Satisfaction | 8 | 0.553 | 4.334 | 7.224 | 0.958 | 3.875 | 1.039 |
0.535 | |||||||
0.616 | |||||||
0.689 | |||||||
0.648 | |||||||
0.676 | |||||||
0.681 | |||||||
0.588 | |||||||
Participation | 6 | 0.566 | 4.306 | 7.177 | 0.876 | 3.317 | 0.893 |
0.706 | |||||||
0.774 | |||||||
0.811 | |||||||
0.807 | |||||||
0.739 | |||||||
Empowerment | 5 | 0.739 | 3.553 | 5.921 | 0.876 | 3.981 | 0.841 |
0.792 | |||||||
0.848 | |||||||
0.843 | |||||||
0.825 | |||||||
Role Ambiguity | 3 | 0.773 | 2.703 | 4.506 | 0.915 | 3.629 | 1.093 |
0.766 | |||||||
0.712 | |||||||
Role Conflict | 3 | 0.870 | 2.589 | 4.315 | 0.853 | 1.994 | 1.027 |
0.890 | |||||||
0.821 | |||||||
Supervisor | 3 | 0.805 | 2.523 | 4.205 | 0.934 | 3.789 | 1.170 |
0.817 | |||||||
0.832 | |||||||
Cooperation | 2 | 0.857 | 1.944 | 3.240 | 0.921 | 3.438 | 1.260 |
0.855 |
Participation | Supervisor | Cooperation | Empowerment | Learning Outcomes | Role Ambiguity | Role Conflict | Satisfaction | Emotional Commitment | Efficiency | |
---|---|---|---|---|---|---|---|---|---|---|
Participation | 1.0 | 0.357 ** | 0.336 ** | 0.112 ** | 0.520 ** | 0.382 ** | −0.114 ** | 0.448 ** | 0.288 ** | 0.535 ** |
Supervisor | 0357 ** | 1.0 | 0.449 ** | 0.150 ** | 0.564 ** | 0.495 ** | −0.207 ** | 0.552 ** | 0.298 ** | 0.526 ** |
Cooperation | 0.336 ** | 0.449 ** | 1.0 | 0.132 ** | 0.446 ** | 0.424 ** | −0.109 ** | 0.437 ** | 0.254 ** | 0.433 ** |
Empowerment | 0.112 ** | 0.150 ** | 0.132 ** | 1.0 | 0.168 ** | 0.104 ** | 0.158 ** | 0.149 ** | 0.175 ** | |
Learning Outcomes | 0.520 ** | 0.564 ** | 0.446 ** | 0.168 ** | 1.0 | 0.627 ** | −0.127 ** | 0.808 ** | 0.571 ** | 0.774 ** |
Role Ambiguity | 0.382 ** | 0.495 ** | 0.424 ** | 0.104 ** | 0.627 ** | 1.0 | −0.251 ** | 0.628 ** | 0.347 ** | 0.570 ** |
Role Conflict | −0.114 ** | −0.207 ** | −0.109 ** | 0.038 | −0.127 ** | −0.251 ** | 1.0 | −0.277 ** | −0.081 ** | −0.125 ** |
Satisfaction | 0.448 ** | 0.552 ** | 0.437 ** | 0.158 ** | 0.808 ** | 0.628 ** | −0.277 ** | 1.0 | 0.542 ** | 0.702 ** |
Emotional Commitment | 0.288 ** | 0.298 ** | 0.254 ** | 0.149 ** | 0.571 ** | 0.347 ** | −0.081 ** | 0.542 ** | 1.0 | 0.531 ** |
Efficiency | 0.535 ** | 0.526 ** | 0.433 ** | 0.175 ** | 0.774 ** | 0.570 ** | −0.125 ** | 0.702 ** | 0.531 ** | 1.0 |
Era | Number | % Recruitment in the Specialization | % COVID-19 Era |
---|---|---|---|
211 | 35.5% | 45.7% | |
166 | 27.9% | 43% | |
217 | 36.5% | 42.9% | |
594 | 100% | 43.9% |
Value | df | Asymptotic Significance (2-Sided) | |
---|---|---|---|
Pearson Chi-Square | 0.925 | 2 | 0.630 |
Likelihood Ratio | 0.924 | 2 | 0.630 |
Linear-by-Linear Association | 0.743 | 1 | 0.389 |
N of Valid Cases | 1354 |
Mean | Std. Deviation | ||
---|---|---|---|
Participation | 1. | 2.9689 | 0.97120 |
2 | 3.4656 | 0.89640 | |
3. | 3.5248 | 0.69218 | |
Supervisor | 1. | 3.3362 | 1.28502 |
2. | 3.9812 | 1.11069 | |
3. | 4.0646 | 0.94782 | |
Cooperation | 1. | 3.0250 | 1.28801 |
2. | 3.4888 | 1.28636 | |
3. | 3.7966 | 1.07927 | |
Empowerment | 1. | 4.1524 | 0.83895 |
2. | 3.8224 | 0.89409 | |
3. | 3.9470 | 0.76831 | |
Learning Outcomes | 1. | 3.3276 | 0.99401 |
2. | 3.8200 | 0.89681 | |
3. | 3.9493 | 0.76863 | |
Role Ambiguity | 1. | 3.3413 | 1.18716 |
2. | 3.7849 | 1.05109 | |
3. | 3.7787 | 0.97684 | |
Role Conflict | 1. | 2.0557 | 0.99542 |
2. | 1.8350 | 1.04106 | |
3. | 2.0527 | 1.02760 | |
Satisfaction | 1. | 3.5929 | 1.13201 |
2. | 3.9903 | 1.03791 | |
3. | 4.0484 | 0.88252 | |
Emotional Commitment | 1. | 3.6286 | 1.15645 |
2. | 3.8283 | 1.09499 | |
3. | 3.8689 | 0.94807 | |
Efficiency | 1. | 3.2525 | 1.05173 |
2. | 3.8727 | 0.87310 | |
3. | 3.8992 | 0.77052 |
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Yfantidou, G.; Spyridopoulou, E.; Papaioannou, A.; Koustelios, A.; Katsoni, V. Sustainable Strategies for Innovative Cooperation in Human Resources Training between the Business Sector and Universities through Internship Programs from the Pre- to Post-COVID-19 Period. Sustainability 2024 , 16 , 7317. https://doi.org/10.3390/su16177317
Yfantidou G, Spyridopoulou E, Papaioannou A, Koustelios A, Katsoni V. Sustainable Strategies for Innovative Cooperation in Human Resources Training between the Business Sector and Universities through Internship Programs from the Pre- to Post-COVID-19 Period. Sustainability . 2024; 16(17):7317. https://doi.org/10.3390/su16177317
Yfantidou, Georgia, Eleni Spyridopoulou, Alkistis Papaioannou, Athanasios Koustelios, and Vicky Katsoni. 2024. "Sustainable Strategies for Innovative Cooperation in Human Resources Training between the Business Sector and Universities through Internship Programs from the Pre- to Post-COVID-19 Period" Sustainability 16, no. 17: 7317. https://doi.org/10.3390/su16177317
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Volume 29, Number 12—December 2023
Work Attendance with Acute Respiratory Illness Before and During COVID-19 Pandemic, United States, 2018–2022
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Cite This Article
Both SARS-CoV-2 and influenza virus can be transmitted by asymptomatic, presymptomatic, or symptomatic infected persons. We assessed effects on work attendance while ill before and during the COVID-19 pandemic in the United States by analyzing data collected prospectively from persons with acute respiratory illnesses enrolled in a multistate study during 2018–2022. Persons with previous hybrid work experience were significantly less likely to work onsite on the day before through the first 3 days of illness than those without that experience, an effect more pronounced during the COVID-19 pandemic than during prepandemic influenza seasons. Persons with influenza or COVID-19 were significantly less likely to work onsite than persons with other acute respiratory illnesses. Among persons with positive COVID-19 test results available by the second or third day of illness, few worked onsite. Hybrid and remote work policies might reduce workplace exposures and help reduce spread of respiratory viruses.
COVID-19 cases in the United States, first reported on January 22, 2020, began to increase in March 2020 ( 1 ). The pandemic resulted in a substantial number of employed persons being laid off or furloughed, especially during spring 2020, and increased prevalence of teleworking ( 2 – 4 ). Employers were advised to actively encourage employees with symptoms of any acute respiratory illness (ARI) to stay home ( 5 ). Both SARS-CoV-2 and influenza viruses can be transmitted by infected persons who are asymptomatic, presymptomatic, or symptomatic ( 6 , 7 ); staying home while ill can reduce workplace virus transmission by reducing contacts between infectious and healthy persons ( 8 ). That policy is considered an everyday preventive action that should be implemented year-round, but especially during annual seasonal influenza seasons and pandemics ( 9 ).
Data collected during the early COVID-19 pandemic (March 26, 2020–November 5, 2020) showed that employed adults with previous telework experience were less likely than those without to work at the worksite (onsite) while sick ( 10 ). However, whether persons worked onsite within the early days of illness when infectiousness is higher has remained unclear ( 7 , 11 , 12 ). We aimed to assess the effects before and during the COVID-19 pandemic of employees’ previous experience with various work-location practices on work attendance patterns within the first 3 days of illness among persons with any ARI, including COVID-19 and influenza. Institutional review boards at the Centers for Disease Control and Prevention and all participating sites approved the study. The enrollees provided informed consent.
Study Population
During November 12, 2018–June 30, 2022, the US Influenza Vaccine Effectiveness Network enrolled adults 19–64 years of age from network-affiliated sites in 7 states. During November 12, 2018–March 18, 2020, persons seeking care for an ARI with cough within 7 days of illness onset were enrolled after local influenza circulation was identified from outpatient facilities affiliated with network sites in 5 states: Michigan (Ann Arbor and Detroit); Pennsylvania (Pittsburgh); Texas (Temple and surrounding areas in central Texas); Washington (Puget Sound region); and Wisconsin (Marshfield, Wausau, and Weston). For the period October 14, 2020–June 30, 2022, case definition was broadened to include persons seeking treatment at outpatient or telehealth facilities within 10 days of illness onset with cough, fever, loss of taste or smell, or seeking clinical COVID-19 testing. Two additional sites, southern California region and Nashville, Tennessee, participated during October 2021–June 2022. For our study, we considered November 2018–March 2020 the period of prepandemic influenza seasons and October 2020–June 2022 the COVID-19 pandemic period. Detailed study methods have been published elsewhere ( 13 – 15 ).
Data Collection
Data were collected from patients at enrollment throughout the entire study period (November 2018–June 2022): date of illness onset, symptoms since illness began (including fever/feverishness), age, sex, race/ethnicity, education, self-rated general health status, cigarette smoking, and number of children <12 years of age living in household. Respiratory specimens were collected from all participants at enrollment and tested for influenza viruses using real-time reverse transcription PCR (rRT-PCR); during the COVID-19 period (2020–2022), specimens were also tested for SARS-CoV-2 using RT-PCR. Persons enrolled on or after January 15, 2022, were asked if they had taken an at-home rapid COVID-19 test while ill and whether the result was positive.
All participants were asked to complete a follow-up survey, either online or over the phone, 1–2 weeks after enrollment. Throughout the 4-year study period, participants were asked at follow-up whether they had fully or mostly recovered from their illness and about employment status, type of employment (hourly, salaried, or other), hours they expected to work and hours usually worked from home in a typical week, and whether the employer discouraged workers with influenza-like symptoms from coming to work ( Appendix Table 1). They were also asked if and where they worked on each of the first 3 days of illness (the first day being the day that symptoms started). Participants were asked about work status for the day before illness onset during November 2018–May 2019 at the Pennsylvania site and at all participating sites for the subsequent study years ( Appendix Table 2). For the period November 2018–September 2021, two sites, in Washington and Wisconsin, did not collect data about work status while ill from participants who typically worked remotely before illness onset. For prepandemic influenza seasons, participants were asked at follow-up whether they worked in a healthcare setting with direct patient contact; that question was asked at enrollment during the COVID-19 pandemic period.
Definitions
To categorize work experience before illness onset for our study, we used responses to questions about the number of hours participants expected to work and usually worked from home in a typical week ( Appendix Figure 1). We categorized as having only onsite experience employed persons who reported that they usually worked no hours from home. We categorized as having hybrid (both onsite and remote) experience persons who stated that hours worked from home were usually fewer than total hours they expected to work. We categorized remaining persons as having only remote experience.
We categorized daily work attendance based on whether persons scheduled to work did or did not work. We categorized persons as scheduled to work for a given day regardless of number of hours for which they were scheduled. Among persons scheduled to work, we categorized those who worked for any number of hours, even if not total hours scheduled, as having worked and remaining persons as having not worked ( Appendix Figure 2). We categorized persons who reported work location for a given day as onsite only or hybrid as having worked onsite.
We classified laboratory-confirmed influenza and SARS-CoV-2 viruses on the basis of positive results from PCR tests. We categorized persons with respiratory symptoms but negative PCR test results for influenza or SARS-CoV-2 as having other ARI.
Assembly of Participants
Among participants, 61% (12,941/21,133) completed the follow-up survey within 28 days of illness onset ( Appendix Figure 3). Survey completion rates were 39% for Texas, 43% for Michigan, 60% for Washington, 75% for California, 75% for Pennsylvania, 79% for Wisconsin, and 89% for Tennessee. Among those who completed the follow-up survey, 69% (8,936/12,941) worked ≥20 h/wk before their illness. After excluding persons missing information on hours usually worked from home before illness or with indeterminate or missing laboratory results, we included 91% (8,132/8,936) in the analysis.
Statistical Analysis
We used χ 2 testing to assess differences between frequencies of categorical variables and Wilcoxon rank-sum test to compare differences in spread and medians ( 16 ). We computed adjusted odds ratios (aOR) for each day by fitting multilevel logistic regression models to account for clustering of participants within study sites using PROC GLIMMIX in SAS version 9.4 (SAS Institute, https://www.sas.com ). We ran 2 sets of regressions for employed persons who were scheduled to work. For the first set of regressions, the dependent variable was having worked at any location. For the second set of regressions, which examined work location to assess the worker’s potential to infect coworkers, the dependent variable was worked onsite. Because persons with remote-only experience before illness onset were unlikely to work onsite while ill, we excluded them from analyses pertaining to work location.
We used a backward selection process using change in –2 log likelihood to assess model fit to determine retention of independent variables in the models and ultimately dropped age, sex, education, and number of children in the household. We then assessed interactions between remaining independent variables ( Table 1 –4; Appendix Tables 7, 8, 9).
During the prepandemic influenza seasons, 1,245 persons had confirmed influenza and 2,362 other ARI ( Appendix Figure 4). During the COVID-19 pandemic period, 114 persons had influenza, 1,888 had COVID-19, and 2,523 had other ARI. Among persons in the study with any respiratory illness, 82.6% with influenza, 61.4% with COVID-19, and 49.6% with other ARI reported having fever.
Among all participants, 14.0% (1,139) had only remote experience before illness onset, 18.5% (1,503) had hybrid experience, and 67.5% (5,490) had only onsite experience ( Appendix Table 3). Hourly workers made up a significantly lower percentage of persons with remote-only (29.9%) or hybrid (21.8%) experience than onsite-only experience (66.6%) (p<0.001). Percentages of participants working in healthcare by location of work experience varied: 7.1% of remote-only, 15.5% of hybrid, and 25.4% of onsite-only personnel (p<0.001). Percentage of participants with at least a bachelor’s degree was significantly higher among persons with remote-only (71.3%) or hybrid (79.5%) experience than those with onsite-only experience (43.5%; p<0.001). Among 1,139 persons with remote-only experience during the study period, most (88.9%) were enrolled during the pandemic period. Among the 1,503 persons with hybrid experience, median hours worked from home in a typical week before illness onset was significantly higher during the pandemic period (16 h/wk) than during prepandemic influenza seasons (8 h/wk; p<0.001).
Approximately three fourths of participants were scheduled to work on each of the first 3 days after illness onset ( Appendix Table 4). Persons with previous remote-only or hybrid experience were significantly more likely than those with only onsite experience to work at any location on the second and third days of illness ( Table 1 ). For example, on the third day of illness during the pandemic period, the percentage who worked at any location was 72.4% for persons with remote-only experience, 65.2% for persons with hybrid experience, and 37.4% for those with onsite-only experience (p<0.001). Among all persons who worked at any location on scheduled work days, median time worked was 8 (interquartile range 8–8) hours for the day before illness and 8 (interquartile range 6–8) hours for each of the first 3 days of illness ( Appendix Table 5). Analysis of the location of work showed that participants were significantly more likely to work remotely on the day before illness onset through the first 3 days of illness during the pandemic period than prepandemic influenza seasons ( Table 2 ). For example, on the third day of illness, 18.5% of persons worked remotely during the pandemic period, compared with 8.8% during the prepandemic influenza seasons.
Participants with hybrid experience were less likely to work onsite than persons with onsite-only experience on the day before through the first 3 days of illness ( Table 3 ); effect magnitude was more pronounced during the pandemic period than prepandemic influenza seasons. For example, for the third day of illness, hybrid versus onsite-only aOR was greater for the pandemic (aOR 0.38, 95% CI 0.29–0.49) than the prepandemic period (aOR 0.69, 95% CI 0.54–0.87; p<0.001 for the work experience–study period interaction term). Conversely, participants were less likely to work onsite during the pandemic period than prepandemic influenza seasons and effect magnitude was more pronounced among persons with hybrid than onsite-only experience. For example, for the third day of illness, pandemic versus prepandemic aOR was greater among persons with hybrid (0.32) than onsite-only (0.59) experience ( Table 3 ). Persons with hybrid experience were more likely to work remotely during the pandemic period than they were during the prepandemic period ( Appendix Table 6). In contrast, persons with onsite-only experience were more likely not to work on scheduled-to-work days during the pandemic than during the prepandemic period. Findings were similar even when we restricted data for the regression models to non–healthcare personnel or the sites that contributed data for all 4 study years ( Appendix Tables 7, 8). Findings were also similar when we restricted the analysis to the sites with highest survey completion rates ( Appendix Table 9).
We stratified the analysis by PCR test results, which showed that the proportion of employees who did not work while ill was greater for persons with influenza or COVID-19 than for persons with other ARI ( Appendix Table 10). During prepandemic influenza seasons, 64.4% of persons with influenza and 40.3% for persons with other ARI did not work on the third day of illness (p<0.001). During the pandemic period, 66.7% of persons with COVID-19 and 48.3% of persons with other ARI did not work on the third day of illness (p<0.001).
For the prepandemic influenza seasons, persons with influenza were significantly less likely than persons with other ARI to work onsite on the second (aOR 0.51, 95% CI 0.43–0.61) and third (aOR 0.39, 95% CI 0.32–0.47) days of illness ( Table 4 ). For the pandemic period, participants with COVID-19 were also significantly less likely than persons with other ARI to work onsite on the second (aOR 0.59, 95% CI 0.49–0.73) or third (aOR 0.31, 95% CI 0.25–0.39) days of illness. Among persons with influenza, COVID-19, or other ARI, those with fever were less likely to work onsite than those with no fever ( Appendix Table 11).
Among persons with COVID-19, substantial percentages worked onsite while ill: 51.2% on day 1, 22.3% on day 2, and 14.1% on day 3 ( Table 4 ). COVID-19–positive PCR test results were available for 1.3% (12/940) by the first day of COVID-19 illness, 10.7% (97/910) by the second day, and 23.5% (211/899) by the third day ( Table 5 ). Persons for whom a positive COVID-19 PCR test result was available by the second day of illness were significantly less likely to work onsite on that day than those whose positive PCR result was available on the third day or later (5.2% vs. 25.0%; p<0.001) ( Table 5 ). Persons for whom a positive PCR test result was available by the third day of illness were significantly less likely to work onsite on that day than those whose positive PCR result was available later than the third day of illness (4.7% vs. 17.2%; p<0.001). Among persons for whom positive PCR test results were available after the second or third day of illness, the percentage who worked onsite was slightly higher when we excluded persons with COVID-19–positive at-home test results by the second or third day of illness ( Appendix Table 12).
During both prepandemic and pandemic periods, adults with remote-only or hybrid experience were more likely to work within the first 3 days of illness compared with those with onsite-only experience. It is notable, however, that persons with hybrid experience were significantly less likely to work onsite on the day before illness through the first 3 days of illness than those with only onsite experience. The effect magnitude of hybrid compared with onsite-only experience on working onsite while ill was more pronounced for the pandemic period than for the prepandemic period. Persons with influenza or COVID-19 were significantly less likely to work onsite on the second and third days of illness than were persons with other ARI. For persons for whom a positive COVID-19 PCR test result was available by the second or third day of illness, few reported working onsite.
Persons with previous remote-only or hybrid experience were significantly more likely to work at any location while ill than those with only onsite experience, enabling a greater level of continuity of work while ill. Greater likelihood of working at any location among persons with hybrid experience than those with only onsite experience has been reported in studies conducted during the 2017–2018 influenza season and during the early part of the COVID-19 pandemic (March–November 2020) ( 10 , 17 ). Remote-only or hybrid experience before illness can enable persons to work remotely if they are well enough, instead of taking sick days.
It is possible that persons without experience working from home were more likely to work in occupations in which remote-only or hybrid work is less feasible and, therefore, workers are less likely to have the option or incentive to work remotely. Those workers might include persons with jobs in hospitality and leisure, transportation, utilities, construction, production, and agriculture ( 18 , 19 ).
Employers were required to provide paid sick leave to workers with COVID-19 during the pandemic ( 20 ). It is unlikely that persons with only onsite experience worked less than persons with hybrid experience after testing SARS-CoV-2–positive because they received paid sick leave. This pattern of persons with only onsite experience working less than persons with hybrid experience was also observed during the pandemic influenza seasons.
Persons with previous hybrid experience were less likely to work onsite the day before illness onset through the first 3 days of illness than persons with only onsite experience, thus reducing the likelihood of workplace exposures to respiratory viruses. A study conducted during the 2017–18 influenza season concurred with that finding, but the study did not examine the likelihood of working onsite on the day before illness ( 17 ). A study conducted during the early part of the COVID-19 pandemic found that persons with hybrid experience were less likely to work onsite while ill than were persons with only onsite experience ( 10 ), an effect more pronounced during the pandemic than the prepandemic period. That difference may have been because of the greater prevalence of telework regardless of illness status during the pandemic ( 3 , 4 ). During the pandemic period, intense public health messaging to stay home when ill, employer policies discouraging or prohibiting employees with ARI symptoms from working onsite, and provision of flexible paid leave for persons with COVID-19 illness may have contributed to the greater effect ( 5 , 20 ).
Persons with laboratory-confirmed influenza or COVID-19 were significantly less likely than persons with other ARI to work onsite on the second and third days of illness. Previous studies have reported similar findings but did not assess the likelihood of working onsite on each of the first 3 days of illness ( 10 , 17 ). Those findings might be attributable to more severe manifestations of illness in persons with influenza or COVID-19 ( 15 ). The finding that the likelihood of working onsite was similar in persons with influenza or COVID-19 compared with persons with other ARI on the first day of illness, as well as the greater likelihood of working onsite on the first day of illness compared with the second or third day of illness, might have been because illness had begun when participants were already at work. For persons ill with COVID-19, having positive PCR test results by the second or third day of illness might have reduced the likelihood of working onsite for several reasons, including being concerned for coworkers, being advised to isolate by case investigators, having employers discourage or prohibit persons with COVID-19 from entering the worksite, and having employers provide flexible sick leave. However, COVID-19–positive PCR test results were available for only a small proportion of persons within the first 3 days of illness because of the lag between illness onset and seeking medical care. At-home rapid COVID-19 tests may enable early testing for persons with symptoms of ARI. Use of at-home tests among persons with COVID-19–like illness in the United States increased from 6% during August 23–December 11, 2021, to 20% during December 19, 2021–March 12, 2022 ( 21 ).
Strengths of our study were that we included data from ≈8,000 persons over a 4-year study period that encompassed both prepandemic and pandemic periods. We obtained respiratory specimens that enabled laboratory confirmation of influenza and SARS-CoV-2. Also, we assessed work attendance within the presymptomatic phase, when persons can be infectious, and the first 3 days of illness, when infectiousness is greatest. One limitation of the study was that 39% of participants did not complete the follow-up survey. However, findings were similar when we restricted the analysis to the sites with the highest survey completion rates. Second, we assessed the proportion of employees who worked at any location within the first 3 days of illness as an indicator of maintenance of workflow. We did not assess how illness may have diminished productivity among persons working while ill versus those working while well. Third, we assessed work attendance only among persons with medically attended ARIs. Findings may not be generalizable to persons who were asymptomatic or who did not seek medical care.
Future research should ascertain productivity in persons who work while ill with influenza or COVID-19. In addition, an assessment of the likelihood of working onsite among persons with ARI who do not seek medical care is needed. Research is also needed on how type of occupation and other workplace policies affect work attendance of sick employees.
In conclusion, working-age adults continue to be at risk for severe COVID-19 ( 22 ). Our study findings show that hybrid work experience before illness onset might give workers the opportunity to continue working but also reduce time worked onsite early in illness, when infectiousness is high. When feasible for a given occupation, employers should consider hybrid and remote work policies that might reduce likelihood of workplace exposures to influenza and SARS-CoV-2 viruses. Such work policies could minimize interaction with infectious persons in workplaces during both the presymptomatic and symptomatic phases of illness and help reduce spread of respiratory viruses.
Dr. Ahmed is a senior science officer at the Division of Global Migration Health, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. His research interests include prevention and control of emerging infectious diseases, including pandemic influenza and COVID-19.
Acknowledgments
We gratefully acknowledge the contributions of the following persons: Chandni Raiyani, Kayan Dunnigan, Kempapura Murthy, Mufaddal Mamawala, Spencer Rose, Amanda McKillop, Teresa Ponder, Ashley Graves, Martha Zayed, Natalie Settele, Jason Ettlinger, Courtney Shaver, Monica Bennett, Elisa Priest, Jennifer Thomas, Eric Hoffman, Marcus Volz, Kimberly Walker, Manohar Mutnal, Arundhati Rao, Michael Reis, Keith Stone, Madhava Beeram, and Alejandro Arroliga. Krissy Moehling Geffel, Rachel Taber, Jonathan Raviotta, Louise Taylor, Michael Susick, GK Balasubramani, Theresa M. Sax, Dayna Wyatt, Stephanie Longmire, Meredith Denny, Zhouwen Liu, Yuwei Zhu. Sally Shaw, Jeniffer Kim. Edward Belongia, Hannah Berger, Jennifer Meece, Carla Rottscheit, Erik Kronholm, Jackie Salzwedel, Julie Karl, Anna Zachow, Linda Heeren, Joshua Blake, Jennifer Moran, Christopher Rayburn, Stephanie Kohl, Christian Delgadillo, Vicki Moon, Megan Tichenor, Miriah Rotar, Kelly Scheffen. Erika Kiniry, Stacie Wellwood, Brianna Wickersham, Matt Nguyen, Rachael Doud, Suzie Park, and Mike Jackson.
This work was supported through cooperative agreements funded by the US Centers for Disease Control and Prevention and by infrastructure funding from the National Institutes of Health (UL1 TR001857) at the University of Pittsburgh.
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- Table 1 . Likelihood of working at any location among adults with COVID-19, influenza, or other acute respiratory illness who were scheduled to work, by work experience in a typical week before illness...
- Table 2 . Reported work location among adults with influenza, COVID-19, or other acute respiratory illness who were scheduled to work, United States, 2018–2022
- Table 3 . Likelihood of working onsite among adults with influenza, COVID-19, or other acute respiratory illness who were scheduled to work, by work experience in a typical week before illness onset, United...
- Table 4 . Likelihood of working onsite among adults who were scheduled to work, by PCR test result, United States, 2018–2022
- Table 5 . Likelihood of working onsite among adults with COVID-19 illness who were scheduled to work, by day when COVID-19–positive PCR test result was available, United States, October 2020–June 2022
DOI: 10.3201/eid2912.231070
Original Publication Date: November 02, 2023
Table of Contents – Volume 29, Number 12—December 2023
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EID | Ahmed F, Nowalk M, Zimmerman RK, Bear T, Grijalva CG, Talbot H, et al. Work Attendance with Acute Respiratory Illness Before and During COVID-19 Pandemic, United States, 2018–2022. Emerg Infect Dis. 2023;29(12):2442-2450. https://doi.org/10.3201/eid2912.231070 |
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APA | Ahmed, F., Nowalk, M., Zimmerman, R. K., Bear, T., Grijalva, C. G., Talbot, H....Uzicanin, A. (2023). Work Attendance with Acute Respiratory Illness Before and During COVID-19 Pandemic, United States, 2018–2022. , (12), 2442-2450. https://doi.org/10.3201/eid2912.231070. |
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What employees say matters most to motivate performance
The past few years have been a confounding time in performance management. Disruptions of long-standing workplace norms have led many employees to rethink their expectations of employers regarding remote work, employee burnout, and work–life balance. Compounding these challenges, an inflationary economy and a slower hiring market have put pressure on employers to “do more” with the talent they already have.
Organizations have responded to this volatility by seeking new formulas to motivate talent, including rethinking their approaches to performance management. Of course, tweaking performance management is not new: McKinsey’s prepandemic research found that most companies had made at least one major change to their approaches in the prior 18 months. But recently, we have seen companies consider more sweeping changes. Some have streamlined goal setting and formal review processes, separated performance and compensation conversations, or simply done away with ratings altogether.
Yet as organizations weigh changes to performance management, it’s difficult to understand what will yield the highest ROI. Leaders are often forced to rely on anecdotal case studies and success stories from others’ experiences to help boost employee motivation to perform. While a plethora of books and articles have been published on the topic in recent years, a “data desert” remains, with a lack of quantitative insights derived from what employees say most inspires and motivates them.
McKinsey’s 2024 performance management survey
Our survey of more than 1,000 employees across the globe sought to shed light on what matters most to employees and offer a new fact base for employers to weigh varied performance management methodologies (see sidebar, “McKinsey’s 2024 performance management survey”). We tested a range of options to understand employee perceptions, including approaches to goals, performance reviews, ongoing development, and rewards.
The survey responses in some cases confirm what intuition has long suggested. In other cases, responses indicate ways to tailor performance management to the unique needs of an organization. Overall, the responses point to essential areas of focus as organizations weigh performance management redesigns. New data helps to better identify options most worthy of investment, based on sources of employee motivation.
A consistent and clearly articulated performance management framework wins the day
The most resonant overall survey finding was this: performance management is most effective when it features strong, consistent internal logic that employees understand.
In recent years, some companies have shifted away from results-based performance management goals and metrics in favor of measures that balance what an employee achieved with how they achieved it. The rationale is partly to make employees feel they are assessed in a more holistic way that considers external factors that contributed to their ability to deliver on a result. The holistic approach also measures how well employees adhered to company cultural norms and leadership expectations. However, the survey results revealed that respondents did not view results-based assessments particularly negatively. Instead, what worked less well were systems without clear and easily understood structures, which respondents viewed as significantly less motivating and fair.
These findings stress that when it comes to building the overall framework for performance management, consistency and simplicity win the day (Exhibit 1). Approaching each element of performance management separately had a lower effect on motivation to perform. Instead, the way the four pillars work together made a difference for respondents. Approaches with a coherent, connected framework across goal setting, performance reviews, feedback, and rewards correlated with the highest motivation to perform. Each company can design a fit-for-purpose approach tailored to the needs of its organization , ensuring core elements are well connected and articulated to employees.
Goal setting has impact when goals are measurable and clearly linked to company priorities
Goal setting has long been accepted as a critical tool for improving performance. The survey puts some hard data behind the decision to invest time and energy into goal setting: 72 percent of respondents cited it as a strong motivator. However, the “what” and “how” of setting those goals are less definitively understood. The survey results shed light on both questions.
What makes an effective goal? The survey revealed that employees felt more motivated when their performance goals included a mix of both individual and team-level goals and when their goals were clearly linked to their company’s goals. Respondents also reported feeling more motivated by goals that felt measurable (Exhibit 2).
However, the survey also suggests that just as important as the content of a goal is the process by which it is set. Employees tended to be more motivated and perceive the performance management approach as fair when they were involved in the process and the goals were updated throughout the year to align with team and company priorities.
These findings suggest high ROI when managers spend time throughout the year counseling employees on updates to align goals with current business priorities and articulating the connection between individual and team goals.
Performance reviews with skilled managers are crucial to employee performance
As employers meet evolving employee expectations, many have rethought their approaches to performance reviews by focusing on changes to ratings. Some have shifted from numerical scales (for example, one through five) to word-based systems (for example, from “underperforming” to “exceeds expectations”) or have done away with ratings altogether.
But the survey showed that different ratings scales (for example, those that measured results versus behavior) yielded negligible differences in how much motivation employees reported.
There was also no significant difference between receiving no rating and receiving a rating on a two-point scale (such as a “pass or fail”) or a three- or five-point scale.
Instead, the survey responses suggest employers may be overemphasizing ratings frameworks and overlooking the criticality of how ratings are given. Our survey indicated employees were significantly more motivated by performance reviews when they were offered by a skilled manager and reflected the individual achievement of a performance goal. This was especially true when managers were involved in setting goals and, therefore, well informed when it came time to assess performance (Exhibit 3).
Investments in manager training to foster meaningful development discussions pay dividends
The survey data also shows how big a difference ongoing development discussion outside the review cycle can make. Only 21 percent of respondents who had no development conversations felt motivated by their companies’ performance management, compared with 77 percent of those who received ongoing feedback.
When it comes to providing feedback, manager training is critical, given that nearly 25 percent of survey respondents said their managers or feedback providers did not have sufficient skills or capabilities to conduct their performance reviews. At large companies (with 10,000 to 50,000 employees), 34 percent of respondents cited this lack of skills. Large companies in particular could designate more power and resources to middle managers —traditionally the most passionate and capable coaches within an organization.
But how can employers empower managers without creating excessive workloads? Because both managers and employees often find the process of providing and receiving feedback taxing , some companies try to limit these exchanges to only once a year. However, given the decisive benefit of regular feedback that our survey revealed, a better approach may be to equip managers with the right tools. Generative AI can make it easier for managers to deliver better feedback —for example, by synthesizing insights from the colleagues who work closely with an employee.
Rewards that include nonfinancial incentives provide a boost
Money matters, of course. But the survey also suggests that, as work–life expectations continue to shift, nonfinancial rewards, like opportunities for upskilling or professional development, can play an increasingly important role in performance management strategies.
The survey showed a strong relationship between employers’ use of both financial and nonfinancial rewards and employees’ perceptions of their personal motivation and performance improvement. The survey also shed light on a unique distinction: employees were more likely to perceive that their organizations’ performance management systems were improving company performance overall when nonfinancial rewards were used. Taken together, these findings suggest that nonfinancial rewards can serve as a critical booster for the success of a cohesive performance management system (Exhibit 4).
Previous McKinsey research has found that nonfinancial incentives should appeal to five sources of meaning : society, client, company, team, and self. These findings align with abundant social science research. 1 Jena McGregor, “What companies get wrong about motivating their people,” Washington Post , November 25, 2016. Nonfinancial incentives could include an immediate manager’s praise, a step-up opportunity to lead a high-profile project, greater autonomy, or more workplace flexibility.
Nonfinancial incentives, like other aspects of an effective approach, should be both frequent and explicitly tied to desired behaviors. They can be used to reward progress toward large, company-wide goals; small, private goals specific to individual employees; or career moves, among other things. Thoughtful deployment of these rewards can help reinforce elements from across the four pillars of a cohesive system.
Economic volatility and shifting workplace norms have sparked many employers’ renewed interest in creating the right performance management formula. Our survey suggests that cohesive overall design and effective execution are the most important focus points.
As organizations consider their approaches across the four performance management pillars—goal setting, performance reviews, ongoing feedback, and rewards—we urge them to pay close attention to the “what” and the “how” to motivate and inspire employees.
Asmus Komm is a partner in McKinsey’s Hamburg office; Brooke Weddle is a senior partner in the Washington, DC, office, where Vivian Breaux is an associate partner; Dana Maor is a senior partner in the Tel Aviv office; and Katharina Wagner is an associate partner in the Berlin office.
The authors wish to thank Karla Martinez and Katherine Boorstein for their contributions to this article.
This article was edited by Katy McLaughlin, an executive editor in the Southern California office.
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COMMENTS
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.
The COVID-19 pandemic, which emerged in December 2019, caused a public health crisis worldwide. On July 28, 2022, the number of confirmed cases was over 571 million, and the death toll was over 6. ...
Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. ... changes that we expect in the wake of COVID-19 for both research and practice. To organize our ... employee preferences but COVID-19 forced many into Mandatory Work From Home (MWFH). Work from Home (WFH). A Gartner (2020) survey ...
Origi N orIGInAl al r esearch Pa P er reseArch PAPer remain in work is therefore an important goal of public health policy.4 ... than the employee; • risk of bias tool (see reporting impact of cOViD-19 on non-lMOs (e.g. job search, food ... Impact of the COVID-19 pandemic on employment and inequalities: a systematic review of international ...
The impacts of COVID-19 on workers and workplaces across the globe have been dramatic. This broad review of prior research rooted in work and organizational psychology, and related fields, is intended to make sense of the implications for employees, teams, and work organizations. This review and preview of relevant literatures focuses on (a ...
Issue Date February 2023. We study how COVID-19 affected the prevalence, expectations, and attitudes toward remote work using specially designed surveys. The incidence of remote work remains higher than pre-pandemic levels and both men and women expect this to persist post-pandemic. Workers also report increased preference for remote work as a ...
An increased level of fear of Covid‐19 was associated with decreased job satisfaction, increased psychological distress, and increased organizational and professional turnover intentions (Rn et al., 2020). In this pandemic of Covid‐19, organizations know that engaged employees are the key to success in this tough time.
Akingbola (2020) explored the impact of COVID-19 on non-profit employees and the need for management strategies such as scenario planning that reflects employees' voices and challenges. However, layoffs, as an organizational strategy during COVID-19, limited their human resources strategy choices when there was no government support to keep ...
This paper is a general literature review, which aims at broadening the scope of management research, by exploring the impact of the COVID-19 on HRM. It identifies the main challenges and opportunities that have arisen from this new pandemic and it offers insights for managers and HRM practitioners into possible future organizational directions ...
The financial and psychological consequences of the Covid-19 have been substantial to many people. As businesses went bankrupt, many lost their jobs, and scores of people worldwide dealt with psychological crises of redundancies, isolation, and loneliness. But the pandemic also came with some opportunities.
Emerging research suggests that work intensification and/or perceived inadequacy of employer support during the COVID-19 crisis has ramifications for employee commitment and turnover intentions (Adamson, Beauregard and Lewis, in press). We invite further research to examine the impact of this social exchange imbalance as another dimension of ...
The COVID-19 pandemic brought unprecedented changes in global work dynamics including mandating telework for most of the U.S. federal workforce to protect employees from health and safety hazards of the communicable virus.
It is evident from emerging scholarly analysis and practitioner discussions that the COVID-19 pandemic has had an indelible impact on the world of work, such that the "post-COVID workplace" will inevitably be very different from the one before (Cooke et al., Citation 2021).In the first half of 2020, the greatest change to work arrangements caused by the pandemic was the shift enmasse to ...
Three themes emerged for RQ1: (1) remote working has an impact on job satisfaction and (2) job satisfaction and the impact remote. working has on job satisfaction is influenced by the number of days an individual works. remotely per week. Two themes emerged for RQ2: (1) COVID-19 has impacted job satisfaction.
Objective: The COVID-19 pandemic made working from home (WFH) the new way of working. This study investigates the impact that family-work conflict, social isolation, distracting environment, job autonomy, and self-leadership have on employees' productivity, work engagement, and stress experienced when WFH during the pandemic.
The COVID-19 pandemic is a persistent global health crisis stemming from the coronavirus disease 2019. On January 30, 2020, the World Health Organization (WHO) officially recognized it as a Public Health Emergency of International Concern and just over a month later, classified it as a pandemic (World Health Organization, 2020).Resulting from the extremely contagious SARS-CoV-2 (severe acute ...
Our paper draws on a holistic perspective of the literature published thus far that has examined the impact of COVID-19 on employee engagement. Furthermore, as new variants of COVID-19 emerge, e.g., Delta, Omicron, COVID-19 will not disappear anytime soon.
The aim of this paper was to study how the COVID-19 pandemic effects felt by employees affected their physical and mental well-being and how these effects impact on the general work performance of employees. ... Another limitation of this research may be that the COVID-19 pandemic effects felt by employees can affect a multitude of other ...
The outcome of the research is expected to worsen as time goes by and the situation and the impact of COVID-19 on the workers group worsen. A qualitative interview with some of the respondents in the research now confessed that COVID-19 have occupied their mind lately with the growing intensity and uncertainty about the potential future impact.
This concept paper reviews the impact of communication and collaboration technologies (CCT) on employee engagement during the Covid-19 pandemic. The concept paper and arguments are based on academic research and will require future research to confirm the conceptual model and propositions. The Covid-19 pandemic is changing human interactions in ...
The ideal worker norm is associated with specific ways of working. The ideal worker is a man who works long hours, is constantly available, and highly productive. Emerging research suggests that the shock of COVID‐19, which forced millions of employees to work from home, may have been powerful enough to disrupt the ideal worker norm. We therefore ask: how did working from home during the ...
The current study investigates well-being from three different aspects during the COVID-19 pandemic in Malaysia: personal, family, and organization. This study is expected to add value to existing well-being research and is pertinent to the ongoing COVID-19 crisis. Therefore, the purpose of the current study is to address the following questions:
A research agenda will be set forth throughout the essay, calling for vocational psychologists to engage in research that fully examines how the COVID-19 pandemic is affecting vulnerable communities.
This literature review aims to systematize the substantial body of research focusing on the impact of the COVID-19 pandemic on remote working arrangements. Due to the limitations imposed by the pandemic, workers suddenly switched from working in an office to remote or home-working.
At the same time, the advent of Industry 4.0 (I4.0) introduced new technologies that might facilitate such activities, mitigating the COVID-19's implications. The objective of this research is two-fold. First, we aim at examining the impact of COVID-19's work implications on employees' performance (i.e. output quality and delivery).
Also, this paper investigated the impact of the COVID-19 Eras on human resource training (HRT) factors and, finally, investigated the correlation between the two variables "Recruitment in the specialization" and "COVID Eras". ... The study suggests that training moderates the impact of HRM practices on employees' performance and that ...
COVID-19 cases in the United States, first reported on January 22, 2020, began to increase in March 2020 ().The pandemic resulted in a substantial number of employed persons being laid off or furloughed, especially during spring 2020, and increased prevalence of teleworking (2-4).Employers were advised to actively encourage employees with symptoms of any acute respiratory illness (ARI) to ...
The COVID-19 epidemic not only impacted China's economy but also induced periodic anxiety among employees, especially during its peak. Even as governmental controls relaxed, enterprises seemed unaffected externally. However, beneath the surface, the lingering effects on employee mental health persisted.
The unfortunate event of the COVID-19 pandemic has provided the opportunity for the largest work-from-home experiment ever happened (Bloomberg, 2020); it has been called "the Great Lockdown," referring to the severe containment measures enforced due to the pandemic outbreak (Khatatbeh et al., 2020).Governments worldwide have taken extreme measures, such as lockdowns, to control the fast ...
The past few years have been a confounding time in performance management. Disruptions of long-standing workplace norms have led many employees to rethink their expectations of employers regarding remote work, employee burnout, and work-life balance. Compounding these challenges, an inflationary economy and a slower hiring market have put pressure on employers to "do more" with the ...