Telework and Face-to-Face Work during COVID-19 Confinement: The Predictive Factors of Work-Related Stress from a Holistic Point of View

  Citation: Soubelet-Fagoaga, I.; Arnoso-Martinez,M.;Elgorriaga-Astondoa, E.; Martínez-Moreno, E. Telework and Face-to-Face Work during COVID-19 Confinement: The Predictive Factors of Work-Related Stress from a Holistic Point of View. Int. J. Environ. Res. Public Health 2022, 19, 3837. https://doi.org/10.3390/ ijerph19073837 Academic Editor: Paul B. Tchounwou Received: 30 January 2022 Accepted: 20 March 2022 Published: 23 March 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). International Journal of Environmental Research and Public Health Article Telework and Face-to-Face Work during COVID-19 Confinement: The Predictive Factors of Work-Related Stress from a Holistic Point of View Iduzki Soubelet-Fagoaga *, Maitane Arnoso-Martinez, Edurne Elgorriaga-Astondoa and Edurne Martínez-Moreno Department of Social Psychology, Faculty of Psychology, University of the Basque Country, 20018 Donostia-San Sebastián, Spain; [email protected] (M.A.-M.); [email protected] (E.E.-A.); [email protected] (E.M.-M.) *Correspondence: [email protected] Abstract: This article explores the socio-labor conditions in which people worked during confinement, analyzing the predictors of work-related stress, according to work modality (face-to-face or teleworking), from a holistic and quantitative (n= 328) point of view. To identify predictors of stress, correlational analyses and multiple hierarchical regressions were conducted with individual, organizational, and societal variables. Furthermore, to analyze the possible modulating role of gender, caregiving, and the level of responsibility in organizations in the relationship between predictor variables and work stress, the macro process of Hayes was used. Our results show that work–family conflict and ruminative thoughts predict stress in both modalities. In teleworking modality, the hours dedicated to work predicted stress, and in face-to-face modality, safety measures and perceived economic threat (tendentially). Being in charge of persons moderated the relationship between ruminative thoughts and economic threat, and stress in face-to-face. Results are discussed by identifying good practices that can improve workplace risk prevention strategies. Keywords: confinement; work-related stress; teleworking; face-to-face 1. Introduction During the confinement period, the work activity of millions of people was precipitously transformed [ 1 ]. Whereas some activities had to be canceled due to the restrictions imposed, others moved their jobs to their homes, with face-to-face activity only continued in cases where it was deemed essential. Specifically, in Spain, 66% of the people who continued their professional activity during confinement continued to go to their workplace, whereas 34% teleworked [ 2 ]. This represented a significant increase and qualitative change in this work modality because before the pandemic, only 4.8% teleworked [ 3 ], and it seems that teleworking was related to the professional group or the status of the job. Thus, people with positions of greater responsibility were more likely to adopt this work modality (60.6%), followed by 21.4% of people with intermediate positions, and only 18% of key workers [ 4 ]. Similarly, although telework increased during confinement, data show that people with higher occupational status had greater access to this type of work [5]. Research in the context of COVID-19 has generated many studies focused on the sociolabor conditions experienced during confinement. Most of these studies have analyzed factors that influenced the occurrence of stress or psychological distress of workers [6–9] . Whereas some have focused on telework [ 6 – 8 , 10 , 11 ], others have focused on face-to-face work, particularly on the socio-labor situation of social-health personnel [ 9 , 12 – 14 ]. However, fewer studies have explored both work modalities together (to our knowledge, three: [ 15 – 17 ]). Furthermore, none of these have analyzed factors related to the occurrence of stress from a holistic standpoint. This perspective allows understanding the extent Int. J. Environ. Res. Public Health 2022,19, 3837. https://doi.org/10.3390/ijerph19073837 https://www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2022,19, 3837 2 of 17 of the concept of stress in its entirety and complexity [ 18 ]. In this regard, this study explores, from an integrated point of view, the explanatory factors of work-related stress and its moderating variables for both face-to-face and teleworkers. From an applied perspective, we have tried to extract lessons that, in the future, could help organizations to prevent occupational risks, and protect the health of their employees. 2. Conceptualization of Stress and Its Predictors Stress has been defined as “a particular relationship between the individual and the environment that is evaluated by the individual as threatening or overwhelming his or her resources and endangering his or her well-being” [ 19 ] (p. 43). In a work context, stress has repercussions at individual and organizational levels [ 20 ], issues that, during the pandemic—and in a context oriented towards maintaining economic activity above all things —were paid less attention than in times of normality. In particular, people who continued to work during confinement (both teleworkers and those who worked outside the healthcare setting), showed high levels of distress (on a scale of 4 ≥ 3), but also reported feeling more stressed than in the context of normality [ 16 ]. Regarding the influence of work modality, the results found to date are inconclusive. Hamouche [ 21 ] found that teleworking was a cause of stress during confinement; Rodríguez et al. (2020) [ 17 ] found lower stress levels among people who combined teleworking with face-to-face work, and found no significant differences between the stress level of teleworkers and those who worked face-to-face. On the other hand, Escudero-Castillo and collaborators [ 15 ] showed that after confinement, the perceived well-being of teleworkers was lower than that of people who worked face-to-face. To understand the causes of stress, this study started from a holistic conceptualization proposed by Durán [ 22 ], where stress in the workplace arises from the confluence of extra-organizational, organizational, and individual factors. Extra-organizational factors include the effects of economic climate, processes of precariousness, and job instability [ 23 ]. In particular, in the context of COVID-19, the occurrence of stress has been related to the economic uncertainty resulting from the pandemic and confinement [ 24 , 25 ]. In this regard, Rodríguez et al. [ 17 ] showed that stress was higher among unemployed people than those who continued with their work. In addition, it should be considered that job insecurity and the economic threat are compounded by variables such as care responsibilities, gender, and the position that employees have in the organization. It has been found that during confinement, the economic threat was a greater concern for families with dependent minors [ 26 ]. Concerning gender, although there are relatively few gender differences in unemployment and the perceived threat of unemployment [ 27 ], women continue to be exposed to more precarious working conditions [ 27 , 28 ]. This situation of greater vulnerability leads us to expect that women will suffer more from the consequences of the crisis caused by the pandemic [ 27 ]. Outside the pandemic context, and in reference to the influence of occupational position, Sora et al. [ 23 ] showed that the perception of fear of dismissal is higher among people with lower-ranking positions. In the context of the pandemic, the stress caused by the economic threat was higher among people with low and middle incomes [24]. This extra-organizational dimension also includes work–family conflict [ 29 , 30 ]. Netemeyer and collaborators [ 29 ] defined this conflict as that which arises when work obligations have repercussions for family care. The pressures arising from employment through different sources generate difficulties in meeting family responsibilities, causing stress among workers [ 30 ]. In the context of confinement, with the closure of schools and without additional resources for the care of dependents, reconciliation took on significant relevance among those who continued to carry out their professional duties [ 31 ]. Most families had increased demands for child and adolescent care, and due to the existing imbalance in care responsibilities, this burden fell mainly on women [32]. Regarding the influence of work modality, the literature on the relationship between telework, work–family conflict, and stress is not entirely conclusive, and it appears that Int. J. Environ. Res. Public Health 2022,19, 3837 3 of 17 telework is both the cause and the solution for reducing the tension between work and care domains [ 33 ]. On the one hand, telework allows for better time management of work, family care, and leisure [ 34 ], since flexibility in organizing the working day is positively valued [35,36] . Some studies have pointed out that people who telework regularly suffer from low work–family conflict [ 37 , 38 ]. Other studies, however, have underlined the difficulties created by the permeability between the work–family domain [ 34 , 38 ]. Concerning the confinement, although some studies (e.g., [ 11 , 39 ]) have shown the benefits of working from home reconciling work with family life, most of them have highlighted the difficulties generated by this. In terms of benefits, Toscano and Zappalà’s [ 40 ] study showed that living with children during confinement positively moderated the relationship between overall performance and remote work productivity. Having to respond to children’s needs would probably make people more likely to work in a more motivating way. Besides, the study carried out by Xiao and collaborators [ 39 ] pointed out both the benefits and risks of working from home with children for mental health. In particular, people who worked from home and who had children in their care were shown to have greater mental well-being compared to people who had not. However, working with children from home also appeared to be a predictor of new mental health issues. Finally, Barriga Medina and collaborators [ 41 ], and Tavares and collaborators [ 11 ], showed that teleworkers suffered high work–family conflict, and that was related to the teleworkers’ burnout [41]. In addition, to explain this conflict, the number of children [ 37 ] and the gender of the teleworker must be considered [ 42 , 43 ]. In general, women with caregiving responsibilities tend to find it more difficult to telework [ 42 , 43 ], a situation that has also been noted during confinement [ 31 ]. In addition, due to the closure of schools and the increasing demand of schooling at home, and the gender imbalance in household chores, Xiao and collaborators’ [ 39 ] study showed that women teleworkers have experienced a higher risk of depression during the confinement. Regarding organizational factors, the predictive role of variables such as insufficient resources to cope with the task [ 44 ], lack of security in the work environment [ 45 ], or work overload [ 20 ] has been studied. Undoubtedly, the arrival of the pandemic brought about a substantial and immediate change in the way work activity continued. This is reflected in the data mentioned above concerning the growth of teleworking in a context in which workers have received little training for such work [ 2 ]. Considering this growth, it appears that the resources provided by organizations, and the capacity of employees to adapt, have been limited. In particular, recent data show that 39.1% of teleworking people indicated that teleworking required more effort than face-to-face work [ 46 ]. Morikawa [ 47 ] states that, in the situation of confinement, the implementation of telework has occurred in a forced manner, without the workers having the necessary resources to carry out this work. In this sense, the research conducted during confinement by Tavares and collaborators [ 11 ] points out that, although teleworkers seem to have adapted easily to the sudden implementation of this modality, among the difficulties experienced is a lack of resources in terms of the necessary infrastructure for teleworking. Similarly, Ruiz-Frutos and collaborators [ 16 ] point out that the workload of most teleworkers increased during confinement, and that this influenced the emergence of stress. Nevertheless, Donati and collaborators [ 48 ] revealed that not all workers experienced teleworking in the same way. In particular, people were more comfortable working from home, and reported higher levels of well-being when they had a large experience in teleworking, and worked in large organizations. It is likely that these workers worked with greater technical and teamwork support, among others. In the case of people whose professional activities had to be carried out from their workplace, given the situation of uncertainty caused by COVID-19, workers and unions demanded minimum safety conditions in the workplace. Despite this, 42.3% of workers indicated not working safely [ 16 ]. Safety at work is a predictor of lower stress, anxiety, and depression [ 49 ]. In the same vein, the literature review conducted by Hamouche [ 21 ] on studies published during the beginning of the pandemic (from December 2019 to Int. J. Environ. Res. Public Health 2022,19, 3837 4 of 17 March 2020) shows the importance of safety measures to ensure the welfare of face-to-face workers, noting that the lower the safety measures, the greater the stress levels. Finally, regarding individual factors, and focusing on the pandemic situation, fear of the disease and the possibility of contagion have provoked ruminative thoughts and compulsive checking behaviors [ 25 ], causing high levels of stress [ 24 ]. Concerning gender, higher levels of risk perception [ 50 , 51 ] and worse self-perceived well-being [ 15 ] have been detected among women than men. In addition, given the concern to transmit the virus to the family, there was greater concern stemming from fear of contagion among those with minor dependents [ 26 , 51 ]. Moreover, considering the exposure to the disease, the perceived threat of health deterioration was particularly significant among those who attended the workplace [52]. 3. Study Objectives and Hypothesis 3.1. Objectives The objective of this study was to explore the socio-labor conditions in which people worked during confinement, analyzing the predictors of work-related stress, according to work modality (face-to-face or teleworking), from a holistic point of view. In particular, to explore the predictors of stress, we analyzed the influence of extra-organizational (perceived economic threat and work–family conflict), organizational (organizational resources available to deal with the changes at work, and the increase (or not) in workload), and individual (ruminative thoughts about the pandemic) factors. In addition, we also sought to explore the modulating role of gender, care, the level of responsibility in organizations, and the income level in the relationships between predictor variables and work stress. In particular, we sought to explore the modulating role of gender and care responsibilities in the relationship between three predictor variables (economic threat, work–family conflict, and rumination) and work stress. As well, we analyzed the modulating role of the level of responsibility in organizations and income level in the relationships between perceived economic threat and work stress. Finally, we examined the modulating role of the organization’s size in the relationship of resources provided by the organizations for teleworking and work stress. We sought to analyze the modulating role of the variables mentioned (and not of all the variables analyzed in this study), since these are the variables that have a theoretical justification for such an analysis. With this, and from an applied perspective, and considering the influence of extraorganizational, organizational, and individual factors in the appearance of work-stress, the aim was to extract some lessons that could help organizations facing possible similar situations in the future. In particular, we wanted to explore how our findings could inform the development of protocols that optimize the organizational response to ensure the occupational health of their employees and prevent, in a targeted manner (depending on the type of work), the occurrence of stress among employees. 3.2. Hypothesis Regarding extra-organizational variables, we expected that perceived economic threat would predict stress in both teleworkers and face-to-face workers (hypothesis 1) [ 24 , 25 ]. Furthermore, considering that fear of the economic crisis caused by the pandemic was higher among people with minor dependents [ 26 ], and that the economic consequences are greater for women [ 27 ], we predicted that taking care of a dependent person (hypothesis 2-a) and gender (hypothesis 2-b) would moderate the relationship between perceived economic threat and stress during confinement. Besides, it was expected that the level of responsibility in organizations (hypothesis 2-c) and income level (hypothesis 2-d) would moderate the relationship between stress and perceived economic threat [ 24 ]. Moreover, given that teleworkers are those with the highest professional status [ 4 , 5 ], we expected that perceived economic threat would be more predictive of stress in people who worked face-to-face compared with those who teleworked (3). Int. J. Environ. Res. Public Health 2022,19, 3837 5 of 17 Work–family conflict was also expected to predict stress in both working modalities (hypothesis 4) [ 31 , 39 , 41 ]. Further, given the gender inequalities in care responsibilities and household chores, and the increased demand for child and adolescent care that confinement entailed [ 31 , 32 ], it was hypothesized that both gender (hypothesis 5-a) and caregiving (hypothesis 5-b) would moderate the relationship between work–family conflict and stress. Concerning organizational variables, we anticipated that for face-to-face workers, security measures for face-to-face work would predict stress (hypothesis 6) [ 49 ]. Furthermore, given the hasty manner in which telework was established [ 47 ], and the fact that this involved greater effort on the part of teleworkers [ 16 , 46 ], it was expected that organizational resources allocated to telework and hours worked (hypothesis 7) would predict stress. At this level, it was expected that the organization’s size would moderate the relationship between organizational resources provided to teleworking and job stress (hypothesis 8) [48]. Concerning the individual rumination variable, it was expected to predict stress in both work modalities (hypothesis 9) [ 24 ]. Finally, given that fear of contagion was higher among women and caregivers [ 26 , 51 ], it was hypothesized that gender (hypothesis 10-a) and caregiver status (hypothesis 10-b) would moderate the relationship between ruminative thoughts and stress. 4. Material and Methods 4.1. Participants The sample consisted of 328 people (M e an = 43.48 years; SD = 10.07), of whom 53.35% were teleworking, and 46.65% were working face-to-face. Of the total sample, 54.6% were women, and 20.6% of workers had caregiving responsibilities, with no differences between men and women. The level of education was high, being statistically higher in those who teleworked (master’s level) compared to those who attended the workplace (degree level) (M = 7.23; SD = 0.9 versus M = 6.36; SD = 1.08) (t = 6.85; p< 0.010). Among people who teleworked, the presence of women was higher (65% vs. 35%) ( χ2 4.51; p< 0.050), whereas among people who worked face-to-face, there were no gender differences (51.5% vs. 48.5%). Regarding responsibility in the organization, the level was significantly higher among people who teleworked (M = 4.04; SD = 1.59 vs. M = 3.44; SD = 1.75) than those who attended the workplace (t = 3.21; p< 0.010), and there were no gender differences in this regard (female teleworkers M = 4.14; SD = 1.41; male teleworkers M = 3.85 SD = 1.82 (t = 1; p= 0.317), and female face-to-face workers M = 3.28; SD = 1.8; male face-to-face workers M = 3.38; SD = 1.85 (t = 0.269; p= 0.788)). In addition, we asked about the income levels of the participants, but due to the sensitivity of the question, we were unable to collect information on this variable. 4.2. Procedure After obtaining approval from the ethics committee of the University of the Basque Country (M10/2020/088), the sample of participants was recruited through an online questionnaire (Survey-Monkey platform) (Survey-Monkey, San Mateo, CA, USA) posted on social networks (Facebook, WhatsApp) (Meta Platforms, Inc, Menlo Park, CA, USA). Data collection was carried out between April and May 2020, during the confinement and state of alarm declared by the Spanish Government. Participants were informed of the study’s objective, asked for permission for the use of the data, and assured of their anonymity and confidentiality. 4.3. Instruments People who teleworked and those who worked face-to-face work answered the same questions, except those related to organizational resources, where specific questions adapted to each work modality were formulated. Sociodemographic characteristics. The following variables were included: gender ( 1 = “Male” , 2 = “Female”), age, taking care of a dependent person (1 = “Yes”, 0 = “No”), Int. J. Environ. Res. Public Health 2022,19, 3837 6 of 17 educational level (1 = “Basic studies not completed”; 8 = “Doctorate”), the level of responsibility in organizations based on a Likert scale (1 = “No responsibility”, 2 = Low level of responsibility, 3 = Medium level, 4 = High level, 5 = “Very high level of responsibility”), family income level (1 = less than 1000 euros per month and 5 = more than 5000 euros), and organization size measured by the number of employees (1 = 1–10 employees, 2 = 11–50, 3 = 51–100, 4 = 101–250, 5 = more than 250). Modality of work. This was determined through one question (“What is your current work situation? “) with the following response options: 1 = “Teleworking,” 2 = “Attending my workplace”. Job stress. This was evaluated through six items of the Stress in General Scale [ 53 ] (“To what extent do you feel the following way in relation to your job?”: “Under pressure”, “Nervous”, “Burdened”, “Calm”, “Comfortable”, “Having difficulty in fulfilling my duties”) (1 = “Not at all”, 7 = “Completely”) (α= 0. 88). 4.4. Extra-Organizational Variables Perceived economic threat. This was measured by an ad hoc scale with two items (“Indicate your degree of agreement or disagreement with the following statements”: “I am afraid of the economic crisis that this pandemic is going to cause”, “I am afraid that this crisis will aggravate social inequality in our society”) (1 = “Strongly disagree”, 7 = “Strongly agree”) (r= 0.47; p< 0.001). Work–family conflict. Three items from the Netemeyer et al. [ 29 ] scale were used (“Indicate your degree of agreement or disagreement with the following statements”: “My work obligations interfere with my family life”, “The time my work demands of me makes it difficult for me to assume my family responsibilities”, “The pressure I have at work makes it difficult for me to assume my family responsibilities”) (1 = “Strongly disagree”, 7 = “Strongly agree”) (α= 0.91). 4.5. Organizational Variables Hours worked. This aspect was determined using a question (“How many hours do you work under these new conditions?”) with three answer options: 1 = “Less than usual”, 2 = “The same”, 3 = “More than usual”; three response options: 1 = “Less than usual”, 2 = “The same”, 3 = “More than usual”. Organizational resources provided by the organizations during teleworking. These were evaluated through five items (“How do you rate the different services that the organization has provided for you to continue working from home?”: “Training”, “Organizational computer”, “Technical advice given”, “Corporate telephone”, “Access licenses to platforms for video-conferencing or collaborative environments”) (1 = “Nonexistent”, 7 = “Totally adequate”) (α= 0.78). Security measures for face-to-face work. These were measured using a seven-item ad hoc scale (“How would you rate the various measures your organization has taken to ensure safety during the pandemic? “Provision of face masks by the company/organization”, “Minimum distance required between workers”, “Gloves provided by the company”, “Provision of means for handwashing”, “Establishment of shifts to avoid crowding of workers”, “Clear information on occupational health measures”, “Structural measures for disinfection of the workspace”) (1 = “Totally insufficient”, 7 = “Totally adequate”) (α= 0.75). 4.6. Individual Variables Ruminative responses linked to the health emergency. Two items adapted from Nolen-Hoeksema and Morrow [ 54 ] were used (“Indicate how often you are feeling each of these sensations during confinement”: “Without wanting to, I am invaded by thoughts and images about what we are experiencing with this pandemic”, “I get distracted or have trouble concentrating because of my thoughts about this pandemic”) (1 = “Never”, 7 = “Constantly”) (r= 0.62; p< 0.001). Int. J. Environ. Res. Public Health 2022,19, 3837 7 of 17 4.7. Data analysis After checking the normality and homoscedasticity of the sample, descriptive analyses were carried out. Next, to identify predictors of stress, correlational analyses and multiple hierarchical regressions were conducted. Given that for the organizational variables, specific questions were developed for each work modality, the analyses were carried out in a segregated manner (for professionals who teleworked and those who worked face-to-face). Sociodemographic variables (gender, taking care of a dependent person, level of responsibility in organizations, organization size, and education level) and extra-organizational variables (economic threat, work–family conflict), organizational variables (hours worked, organizational resources provided by the organizations for teleworking and safety measures for face-to-face work), and an individual variable (rumination) were included. Finally, in order to analyze the modulating role of gender, caregiving, level of responsibility in organizations, and organization size in both telework and face-to-face work, the macro process of Hayes et al. (Dubuque, IA, United States) [ 55 ] was used. The Hayes et al. macro process allows for moderation analysis to be conducted in SPSS (IBM, Madrid, Spain). Work stress was introduced into the model as a dependent variable; economic threat, work–family conflict, rumination, and the resources provided by the organizations for teleworking as independent variables; and gender, caregiving, the level of responsibility, and organization size as modulating variables. 5. Results 5.1. Descriptive According to the Modality of Work Table 1presents the variables studied according to work modality. Table 1. Means, and T de Student and chi-squared test results according to work modality. Variables Total n= 328 Telework n= 175 Face-to-Face Work n= 153 T de Student/ Chi-Squared pd de Cohen/Phi M(SD)/% M(SD)/% M(SD)/% Stress at work 4.26(1.37) 4.14(1.32) 4.4(1.43) −1.595 0.112 −0.19 Perceived economic threat 6.1(1.03) 6.02(1.07) 6.19(0.97) −1.325 0.186 −0.16 Work–family conflict 3.52(1.74) 3.62(1.69) 3.39(1.81) 1.103 0.271 0.13 Organizational resources to telework - 3.82(1.53) - Safety measures for on-site work - - 4.53(1.41) Rumination 3.25(1.44) 3.07(1.41) 3.49(1.45) −2.384 0.018 −0.29 Hours worked 2.04(0.71) 2.07(0.78) 1.98(0.64) Less 23.6% 25.5% 21.2% 0.733 0.392 −0.50 Same 48.5% 40% 59.1% 10.701 0.001 0.190 More 27.9% 34.5% 19.7% 8.029 0.005 −0.164 5.2. Predictors of Work Stress According to Work Modality Table 2presents the correlations between work stress and the set of variables studied according to work modality. Work stress correlated positively and significantly with perceived economic threat, work–family conflict, hours worked, and rumination in both work modalities. Likewise, in both work modalities, stress correlated negatively with the provision of lower levels of organizational resources (for teleworking) and security measures (for working on-site). The variables that correlated with work stress were then entered into the hierarchical regression analysis, grouping them according to the extra-organizational, organizational, and individual categories in which the variables had been included. Among teleworkers, work–family conflict, hours spent at work, and rumination were found to be predictors of work stress (see Table 3). Int. J. Environ. Res. Public Health 2022,19, 3837 8 of 17 Table 2. Correlations between work-related stress and extra-organizational, organizational, and individual variables according to work modality. Variables Stress at Work Teleworking Going to the workplace Gender 0.106 0.178 Caregiving 0.134 0.075 Level of education 0.100 0.121 Level of responsibility −0.049 0.098 Organization size 0.083 0.083 Economic threat perceived 0.165 * 0.234 * Work–family conflict 0.498 ** 0.509 ** Organizational resources for teleworking −0.221 ** Safety measures for on-site work −0.478 ** Hours worked 0.245 ** 0.340 ** Rumination 0.360 ** 0.366 ** Note. **. Correlation is significant at the 0.01 level (bilateral). *. Correlation is significant at the 0.05 level (bilateral). Table 3. Hierarchical regression on work-related stress among teleworkers. R2B Standardized Sig 95% CI (LL, UL) Collinearity Statistics VIF Tolerance Model 1 0.238 Perceived economic threat 0.119 0.108 (−0.030, 0.295) 0.967 1.034 Work–family conflict 0.463 0.001 (−0.239, 0.459) 0.967 1.034 Model 2 0.267 Perceived economic threat 0.156 0.037 (0.011, 0.334) 0.936 1.068 Work–family conflict 0.388 0.001 (0.176, 0.408) 0.840 1.190 Organizational resources −0.128 0.091 (−0.228, 0.017) 0.904 1.106 Hours worked 0.153 0.040 (0.012, 0.496) 0.934 1.071 Model 3 0.318 Perceived economic threat 0.075 0.320 (−0.081, 0.248) 0.842 1.188 Work–family conflict 0.340 0.001 (0.142, 0.370) 0.811 1.233 Organizational resources −0.108 0.141 (−0.207, 0.030) 0.898 1.113 Hours worked 0.193 0.009 (0.083, 0.557) 0.909 1.100 Rumination 0.258 0.001 (0.097, 0.371) 0.817 1.223 Among face-to-face workers, work–family conflict, security measures, and rumination explained the variance in work stress. In addition, perceived economic threat predicted job stress in a tendential manner (see Table 4). Table 4. Hierarchical regression on work-related stress among people with face-to-face jobs. R2B Standardized Sig 95% CI (LL, UL) Collinearity Statistics VIF Tolerance Model 1 0.297 Perceived economic threat 0.179 0.029 (0.028, 0.495) 0.984 1.016 Work–family conflict 0.505 0.001 (0.264, 0.509) 0.984 1.016 Model 2 0.426 Perceived economic threat 0.182 0.014 (0.054, 0.477) 0.981 1.019 Work–family conflict 0.359 0.001 (0.154, 0.395) 0.829 1.207 Safety measures 0-.353 0.001 (−0.499, −0.202) 0.918 1.090 Hours worked 0.146 0.057 (−0.011, 0.673) 0.898 1.114 Model 3 0.478 Perceived economic threat 0.125 0.083 (−0.024, 0.391) 0.928 1.078 Work–family conflict 0.331 0.001 (0.138, 0.368) 0.819 1.221 Safety measures −0.356 0.001 (−0.495, −0.212) 0.918 1.090 Hours worked 0.106 0.152 (−0.090, 0.571) 0.874 1.144 Rumination 0.248 0.001 (0.103, 0.391) 0.887 1.128 Int. J. Environ. Res. Public Health 2022,19, 3837 9 of 17 5.3. Moderation Analysis Results The caregiving variable modulated the relationship between perceived economic threat and job stress in the face-to-face work modality ( β = 1.39, SE = 0.439, t = 3.171, p= 0.02 ). In particular, the positive relationship between perceived economic threat and job stress was more pronounced in those who have dependents under their care (Figure 1). 6.00 5.50 5.00 4.50 4.00 3.50 3.00 5.60 5.80 6.00 6.20 6.40 6.60 6.80 7.00 Perceived economic threat Care Job stress Figure 1. Influence of perceived economic threat on work-related stress as a function of caregiving in a face-to-face work setting. The model including caregiving and perceived economic threat explained 16% in the variance of job stress (R2 = 0.16, F(3100) = 6.45, p= 0.005, f2 = 0.19), and the interaction explained an additional 8% in the variance in job stress (change in R2 = 0.08, F(1100) = 10.13 , p= 0.01). The caregiving variable also modulated the relationship between rumination and job stress in the face-to-face work modality ( β = 0.53, SE = 0.23, t = 2.291, p= 0.02). The positive relationship between rumination and work stress was also more pronounced in those who have dependents under their care (Figure 2). The model including caregiving and rumination explained 18% in the variance of job stress (R2 = 0.18, F(3100) = 7.37, p= 0.002, f2 = 0.22), and the interaction explained an additional 4% in the variance in job stress (change in R2 = 0.04, F(1100) = 5.13, p= 0.03). In the relationship between work–family conflict and stress, caregiving and gender did not moderate this relationship in any population analyzed. In addition, the level of responsibility in organizations did not moderate the relationship between perceived economic threat and work-related stress. Finally, none of the moderation analyses yielded significant results in the case of the teleworking population. Int. J. 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