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Attribution License (COVID-19 Pandemic and Mental Health
According to the World Health Organization (WHO, 2019), COVID-19 is an infectious disease caused by the recently discovered coronavirus. The outbreak of the epidemic was unleashed in Wuhan (China) in December 2019, and before this, the virus and the disease caused by this virus were unknown. Nowadays, there is a pandemic that has affected many countries around the world.
Due to this situation, a huge number of countries decreed a mandatory quarantine. Specifically, in Argentina, the Preventive and Obligatory Social Isolation (ASPO), by decree 297/2020, began on March 19th, 2020 (Ministry of Health of the Nation, 2020) and ended on November 9th, 2020. In the months of June and July 2020, 95% of the country's infections were registered in the Metropolitan Area of Buenos Aires (AMBA). The AMBA is an urban conglomerate made up of the City of Buenos Aires and the 40 municipalities of the province of Buenos Aires that surround it. It concentrates 37% of the country's population (14,800,000 inhabitants according to the last population census of 2010) and 40% of economic activities (Zusman, 2020). This situation implied a change in their routine, forcing people to stay in their usual residences and to refrain from going to their places of work, limiting circulation on roads, paths and public spaces (Macías, 2020).
Social distancing, complementary hygiene measures, the suspension of non-priority activities and the proliferation of misinformation generated a new environment that established certain demands and demands for action on people. These demands are potential stressors and may trigger the stress process, which could be called pandemic stress. In this situation, Macías (2020) defined pandemic stress as a psychological state produced by an adaptation process where the individual values the demands or demands of the environment, determined by the pandemic, as overflowing with their resources to perform them effectively. This generates the appearance of a set of symptoms or reactions that show or manifest the personal imbalance generated by the stress that is being experienced. Finally, the individual must take actions to mitigate or make that stress more manageable (Macías, 2020).
Caballero Domínguez and Campo-Arias (2020) carried out a study about how social distancing would generate both adaptive reactions, typical of the balance and homeostasis processes of the individual being, as well as maladaptive ones. In a way, the conditions through which social isolation is generated and carried out are configured as a non-normative stressor, capable of increasing the possibility of presenting psychiatric nature problems for the first time or of increasing or exacerbating pre-existing disorders.
Although reactions to a pandemic are usually presented as acute, it is possible to observe symptoms or long-term emotional sequelae. They depend essentially on various individual variables, such as intolerance to uncertainty, perceived vulnerability to illness, or propensity for anxiety disorders. It is emotional stress that, to a large extent, ends up generating neurobiological consequences that would increase the probability of exacerbating concomitant diseases and the vulnerability to meet criteria for a specific disorder or pathology, particularly anxiety and depression (Caballero Domínguez & Campo-Arias, 2020).
Work and Economy
The interest in unemployment and its respective repercussions has its genesis in the great financial crises of the beginning of the 20th century. Nowadays, it takes on special relevance given the context of the COVID-19 pandemic, which promotes a panorama of uncertainty at all levels, including social security, the economy, employment, and family well-being. The scenario has changed substantially in recent years, therefore this will keep changing in accordance with the global health panorama, fundamentally affecting the economy and work (Ahumada, 2020; Molina-Quiroz, 2020). According to Llorente (2020) the effect of the pandemic on the labor market is unprecedented, that in the case of developed countries such as Spain, a very intense temporary impact was forecast during the following months to the extent that the confinement tended to decline and projected the total recovery of the labor market up to a year later, being slow and gradual, they expressed that the labor groups most affected or vulnerable to the health crisis would be women employed in the Commerce, Hospitality and Tourism sectors, young people, workers over 45 years of age, immigrants, temporary workers and less qualified workers. And according to Laporte et al. (2020) in Latin America the figure is alarming, the impact produced by the COVID-19 pandemic generated the closure of 2.7 million companies, equivalent to 19% of companies in the region, and the unemployment of more than 8.5 million people (CEPAL, 2020).
In accordance with what was stated above to COVID-19 context, the economy was affected in all countries, which generated critical situations in different companies around the world, as well as unemployment and economic difficulties in most of the families and individuals. Those subjects with a high anxiety trait, that is, they tended to respond with anxiety to situations of uncertainty, could be overwhelmed by the economic situation generated by this pandemic (Cedeño et. al, 2020).
The International Labor Organization (ILO) explains that the policies which were taken to face the crisis have generated a strong trade decline that affects all production value chains. This situation, along with the high number of unemployed people, places Argentina in a very vulnerable situation to the impact of the crisis caused by COVID-19. The cessation of almost all activities in the country, the restricted mobility of the inhabitants, and since people are reducing their consumption to basic needs, have caused the closure of practically all stores and businesses (Ernst & López Mourelo, 2020).
Non-essential economic sectors have slowed down their operations as several cannot operate if their workforce must remain in their homes. Due to the profound impact on the labor structures associated to these companies, many have been forced to suspend contracts and grant early vacations or, in the worst case, to fire their workers (Gutiérrez et al., 2020).
In Argentina, microenterprises and SMEs are particularly important as creators of decent employment, for economic growth and productive development (ILO, 2012). According to a recent study by the Observatory of SMEs (2020), the 58% of the companies surveyed report having suffered a considerable drop in sales, especially in their commercial areas as well as independent professionals.
The ILO explains that the health crisis caused by COVID-19 came to Argentina at a time of economic and social fragility. The government was in the process of renegotiating its public debt, which reached unsustainable levels. This occurred in a context of negative economic growth and a high level of inflation, with an interannual variation of 50.3% registered in February 2020 (INDEC, 2020), which put pressure on companies, especially SMEs. As a result, the labor market was weakened with a high unemployment rate, particularly among young people, added to a high informality of the economy, which generated precarious employment for a large part of the population (Ernst & López Mourelo, 2020).
In Argentina, most labor institutions are designed to primarily cover formal salaried workers. In this context, shocks like the current one, which hit the labor market hard, leave a large percentage of the country's workers in a situation of very low or null protection. Consequently, it is estimated that the crisis caused by the COVID-19 pandemic will have a strong impact on the labor market in that country, which was already in a very weak situation before this health emergency.
In addition, the gender labor gaps are alarming. Women suffered the highest levels of unemployment and job insecurity. In Argentina, they earn 29% less than their male peers, a difference that widened for informal wage earners, reaching 35.6%. On the other hand, around 96% of the people who receive the Universal Child Allowance (AUH) are women, which is linked to a significant number of female heads of household. Contexts where women are solely responsible for children and adolescents. adolescents: 85.6% of these households are single mothers (Lobato, 2020).
In this scenario, studies related to gender differences evidence the unexpected increase in teleworking which coincided with an unprecedented multiplication of domestic work and family responsibilities (Actis di Pasquale et al., 2021). Research carried out during the COVID-19 crisis on the impact of the aforementioned aspects, measures points to a clear increase in gender inequalities (Power, 2020; Qian & Fuller, 2020). In this way, the segregation of the labor market, the greater burden of domestic and care work, the greater social exclusion, sexist discrimination and the lesser presence in decision-making spaces would subject women to higher levels of stress and depression, and it would limit their possibility to access resources that can protect their mental health (Bacigalupe et al., 2020; Borrell et al., 2014; Ussher, 2010).
The Present Study
In general, the field of mental health and well-being is not considered as a priority, not enough resources are provided to manage or mitigate the effects of pandemics at this level. It is understandable that this happens in the acute phase of an outbreak, but psychological and psychiatric needs must be addressed during all phases of pandemic management (Usher et al., 2020).
This disease has made it clear that, as proposed by the WHO, health is not exclusively biological, nevertheless is a complete biological, psychological, and social well-being. Considering this, it is necessary then to analyze the situation from a psychological point of view. Thus, psychology’s contributions are crucial in the fight against COVID-19 from its foundations, principles and scientific evidence (Michie et al., 2020).
In this regard, Ernst and López Mourelo (2020) explain the importance of focusing on two immediate objectives for political responses to the crisis. In the first place, they must ensure the health of the workers, employers and their families and minimize the risks of spreading COVID-19. In second place, rapid and coordinated global actions must be taken to sustain jobs, income, as well as the stimulation of the economy and the demand for employment.
To achieve the first objective proposed by these authors, it is important to determine how psychological variables behave, focusing on the inherent aspects of the work, as a sphere that has clearly been negatively impacted by COVID-19. For this reason, the present study had as objectives: a) Describe Pandemic Stress and Depression, b) Evaluate the existence of relationships between these variables, c) Determine significant differences according to gender, employment situation, company size, work modality and possibility of closure their business during ASPO.
From the results, it is expected to find a positive association between pandemic stress and the depression reported by the respondents. What is more, it is thought that when it comes to gender, women would have reported higher levels of stress and depression compared to men. Similar to these, it is thought that those people who were unemployed, or who have thought about closing their businesses, would be those who show the highest levels of depression and stress mentioned above. Finally, it is expected that all those surveyed who have worked from home experience a lower level of pandemic stress than those who work outside.
Method
Participants
The sample consisted of 494 adults, 74.7% female (n = 369) and 25.3% male (n = 125), with a mean age of 36.2 years (SD = 12.3, range = 18–70) from Buenos Aires Metropolitan Area (AMBA) completed the survey voluntarily and anonymously. Regarding educational level, 3% (n = 15) of the participants unfinished high school, 15% (n = 74) finished high school, 12.6% (n = 63) had tertiary level education studies, 34.2% (n = 167) unfinished university-level studies and 35.2% (n = 175) completed a university degree course.
About the description of the sample on the labor situation, 45% (n = 219) were employed, 18.4% (n = 92) unemployed and 36.6% (n = 175) were self-employed workers/owners. In addition, 54.9% (n = 218) of the participants saw their income affected. The predominant work modality of the participants was Home Office with 63.3% (n = 239) of the sample.
Those who were medicated with antidepressant psychotropic drugs were excluded from the sample. The data was collected from August 11th, 2020 to September 2nd, 2020 during Preventive and Obligatory Social Isolation (ASPO).
Instruments
Sociodemographic Questionnaire
Age, gender, level of education, place of residence and marital status were investigated.
Other Variables
To explore employment status, company/business size determined by the number of employees (micro = up to 5 employees, small = 6 to 50 employees, median = 51 to 200 employees, large = more than 200 employees), work modality (Homeoffice/Out of home), possibility of closure their business during ASPO, presence of disease/s and psychological/psychiatric treatment.
SISCO Inventory of Pandemic Stress
The SISCO Inventory of Pandemic Stress (ISEP; Macías, 2020) assesses the stress generated by the demands of the COVID-19 pandemic environment, consisted of 15 items with a forced choice form: Five for the Stressors section (from 1 to 5) with statements such as "That hospitals do not have the resources to care for the sick" and "That our health system collapses", five for the Symptoms or Reactions section (from 6 to 10) such as "Anguish" and "Lack of sleep" and five for the Coping Strategies section to avoid contagion, and which are interpreted as factors causing stress, with statements such as "Having as little contact as possible with people" and "Continuously washing hands" (from 11 to 15). They are all answered by a six-value Likert-type scaling where 0 is “Not at all” and 5 is “A lot”. This inventory was validated by Caccia et al. (2021) in the Argentine context, showing evidence of reliability in Cronbachs’s alpha of .66 to .82, and construct validity through confirmatory factor analysis that shows a bi-factorial model as most appropriate. For the present sample, the global scale composed of the 15 items presented reliability in Cronbach's alpha of .78.
The mean is transformed into a percentage and the result is interpreted with the following indicative scale: 1) From 1% to 20%: very slight level, 2) From 21% to 40%: mild level, 3) From 41% to 60%: moderate level, 4) From 61% to 80%: strong level, and 5) From 81% to 100%: very strong level of pandemic stress.
Beck's Depression Inventory (BDI-II)
Beck's Depression Inventory (BDI-II) Argentine adaptation (Brenlla & Rodríguez, 2006) is a 21-item, self-rated scale that evaluates key symptoms of depression including mood, pessimism, sense of failure, self-dissatisfaction, guilt, punishment, self-dislike, self-accusation, suicidal ideas, crying, irritability, social withdrawal, indecisiveness, body image change, work difficulty, insomnia, fatigability, loss of appetite, weight loss, somatic preoccupation, and loss of libido. Individual scale items are scored on a 4-point continuum (0 = least, 3 = most), with a total summed score range of 0–63. Higher scores indicate greater depressive severity. Two subscales include a cognitive-affective subscale and a somatic-performance subscale. Brenlla and Rodríguez (2006) adaptation yielded a Cronbach's alpha of .93. For the present sample the Cronbach’s alpha was .91.
Procedure
An online survey was used to collect data. It was disclosed through social networks such as Facebook, Instagram and WhatsApp. After agreeing to participate through informed consent, the questionnaires were presented in the same order for all participants. The time required to complete them was approximately 10 minutes. The procedures recommended by the American Psychological Association (2002) were considered and the ethical principles of research with human beings of the Declaration of Helsinki (Mundial, 2014) were respected, ensuring the necessary conditions to protect the confidentiality of the participants.
Data Analysis
Nonparametric test was performed as the distribution of some of the scores was not normal, using Multivariate Analysis of Variance (MANOVA) due to the evidence of its robustness in the event of non-compliance with the normality assumption (Blanca et al., 2017; Salkind, 2010; Schmider et al., 2010). This statistical method offers the possibility of including control variables such as age and educational level. In addition, Spearman’s rho correlations and Cronbach's Reliability Analysis were performed. The level of significance was established for all analyzes at α = .05. Statistical analysis was conducted using the SSPS program (21 version).
Results
Description
Frequency of Depression and Pandemic Stress
The levels of depression that the participants presented were 54.5% (n = 269) with a minimal-mild level and 45.5% (n = 255) with a moderate-severe level. Of the total sample, 2.8% (n = 14) showed a very mild or mild level of pandemic stress, 15% (n = 74) presented a moderate level while most people surveyed, 82.2% (n = 406), evidenced a strong or very strong level of pandemic stress.
Descriptive Statistics of the Variables
On average, the men surveyed reported a mild level of depression, a strong level of pandemic stress, stressors and coping strategies, and a moderate level of reactions or symptoms. Instead, women showed a moderate level of depression, a strong level of pandemic stress, reactions and coping strategies, and a very strong level of stressors. It can be seen in Table 1.
Table 1
Descriptive Statistics
| Variable | Male
|
Female
|
||||||
|---|---|---|---|---|---|---|---|---|
| M(SD) | 95% CI | Range | n | M(SD) | 95% CI | Range | n | |
| Depression | 17.03(11.50) | [14.99, 19.06] | 0–50 | 125 | 21.76(12.29) | [20.50, 23.02] | 0–56 | 369 |
| PS | 50.05(11.51) | [48.01, 52.09] | 23–73 | 125 | 56.14(9.54) | [55.16, 57.12] | 21–75 | 369 |
| Stressors | 18.56(5.09) | [17.65, 19.46] | 4–25 | 125 | 20.68(4.40) | [20.23, 21.13] | 5–25 | 369 |
| Reactions | 13.93(5.87) | [12.89, 14.97] | 0–25 | 125 | 16.17(5.41) | [15.62, 16.73] | 0–25 | 369 |
| CS | 17.56(5.27) | [16.62, 18.49] | 2–25 | 125 | 19.28(4.24) | [18.84, 19.71] | 4–25 | 369 |
Note. CI = Confidence Interval; PS = Pandemic Stress; CS = Coping Strategies.
Associations
Due to the Age association analysis is negative with Depression (rho = -.341, p < .021) and positive with Coping Strategies (rho = .168, p < .036), partial correlations were carried out, controlling for the age variable. In addition, the level of education was controlled since a significant correlation was found with stressors (rho = -.170, p < .035), and with coping strategies (rho = .109, p < .039). The results show significant and direct correlations between the levels of Depression and Stress of the pandemic (rho = .476, p < .001), the levels of Depression linked to Stressors (rho = .266, p < .011) and the levels of Depression linked to Reactions (rho = .567, p < .000). As can be seen, Depression is significantly associated with all variables except Coping Strategies.
Comparisons
Due to the correlations between the psychological variables, and the age and educational level, the need of using control variables was determined for each analysis. Age was controlled for comparison according to gender, level of education for the type of work and company size, and both variables for the employment situation. For the comparison according to the possibility of closure, the Games-Howell post-hoc test was used because of the homogeneity of variances was not found and there was no need to use a control variable.
Then, the Levene equality test was carried out, the results of which showed that the variable Pandemic Stress (p < .007) and the Stressors (p < .013) and Strategies (p < .001) dimensions were not homogeneous variance. To comply with this requirement, Johnson transformations were held on Pandemic Stress (p < .709), Stressors (p < .977) and Strategies (p < .330), using the tool developed by Hemmerich (2016).
Based on the results obtained in the analysis of difference according to gender, a significant difference is observed in all the variables, with female persons being the ones who score the most in each one of them. Regarding the size of the effect (Eta2) both for Depression and for Reactions, this size is small. In contrast, for Pandemic Stress, Stressors and Strategies, the effect size would be medium (Cohen, 1988). It can be seen in Table 2.
Table 2
Comparison of Variables According to Gender
| Variable | Female (n = 369)
|
Male (n = 125)
|
F | p | Eta2 | ||
|---|---|---|---|---|---|---|---|
| M | SD | M | SD | ||||
| Depression | 21.76 | 12.29 | 17.03 | 11.50 | 6.98 | .01 | .01 |
| Pandemic Stress J | .20 | .99 | -.37 | 1.03 | 32.51 | .00 | .06 |
| Stressors J | .11 | .89 | -.30 | .93 | 22.63 | .00 | .04 |
| Reactions | 16.18 | 5.41 | 13.94 | 5.87 | 11.26 | .00 | .02 |
| Strategies J | .06 | .91 | -.27 | .99 | 17.81 | .00 | .04 |
Note. J, M, Y, SD after a Johnson transformation. The Bonferroni fit was used.
As can be seen in Table 3, those who thought at some point during the quarantine of closing their business, commerce, entrepreneurship, among others, were the ones who presented the most Depression and Reactions levels to pandemic stress. A large effect size is observed for Depression, medium for Reactions, and small for the rest of the variables (Cohen, 1988).
Table 3
Comparison of Variables According to Possibility of Closure
| Variable | Yes (n = 63)
|
No (n = 92)
|
F | p | Eta2 | ||
|---|---|---|---|---|---|---|---|
| M | SD | M | SD | ||||
| Depression | 21.90 | 11.42 | 14.47 | 10.31 | 16.50 | .00 | .10 |
| Pandemic Stress | 55.34 | 9.74 | 52.52 | 11.50 | 2.35 | .13 | .02 |
| Stressors | 20.14 | 3.80 | 19.45 | 5.27 | .72 | .40 | .01 |
| Reactions | 16.29 | 5.09 | 13.76 | 6.42 | 6.35 | .01 | .04 |
| Strategies | 18.91 | 4.70 | 19.31 | 4.45 | .27 | .61 | .00 |
Note. The Games-Howell post-hoc test was used.
Regarding its own internal work structure, those who worked under the Home Office modality had a higher level of PE and use of Coping Strategies than those who worked outside the home. On the other hand, a small effect size was found in EP, while for Strategies it was large (Cohen, 1988). It can be seen in Table 4.
Table 4
Comparison of Variables According to Work Modality
| Variable | Home Office (n = 239)
|
Out of home (n = 102)
|
F | p | Eta2 | ||
|---|---|---|---|---|---|---|---|
| M | SD | M | SD | ||||
| Depression | 18.42 | 11.61 | 18.98 | 12.41 | 0.04 | .84 | .00 |
| Pandemic Stress J | 0.09 | 1.07 | -0.19 | 1.10 | 5.93 | .02 | .02 |
| Stressors | 19.84 | 4.77 | 20.22 | 4.83 | 0.01 | .92 | .00 |
| Reactions | 14.86 | 5.88 | 15.16 | 5.90 | 0.15 | .70 | .00 |
| Strategies J | 0.24 | 0.89 | -0.50 | 0.95 | 44.74 | .00 | .12 |
Note. J, M and SD after a Jonhson transformation.
As can be seen in Table 5, the employees of micro, small and medium-sized companies presented a higher level of stressors than the employees of large companies. The effect size is interpreted as small (Cohen, 1988).
Table 5
Comparison of Variables According to Company Size
| Variable | MSMEs (n = 122)
|
Large (n = 109)
|
F | p | Eta2 | ||
|---|---|---|---|---|---|---|---|
| M | SD | M | SD | ||||
| Depression | 18.76 | 11.41 | 20.20 | 11.61 | 1.83 | .18 | .01 |
| Pandemic Stress | 53.97 | 10.74 | 54.60 | 11.21 | 0.40 | .53 | .00 |
| Stressors J | 0.19 | 0.90 | -0.12 | 0.96 | 4.35 | .04 | .02 |
| Reactions | 14.84 | 5.90 | 15.84 | 5.42 | 2.10 | .15 | .01 |
| Strategies | 18.13 | 5.01 | 19.38 | 4.50 | 3.66 | .06 | .02 |
Note. J, M and SD after a Johnson transformation.
About the differences according to the employment situation, in Table 6 it can be appreciated that some significant differences were found in all the variables except in the Coping Strategies. When investigating the pairwise comparisons, it is possible to find that in Depression, EP, E and R, there is no significant difference between employed and self-employed, there is between the latter and the unemployed, who score the highest in the four variables. The effect size for Depression was medium, while for the rest of the variables it was small (Cohen, 1988).
Table 6
Comparison of Variables According to Employment Situation
| Variable | Employee (n = 219) |
Unemployed (n = 92) |
Freelance (n = 175) |
F | p | Eta2 | |||
|---|---|---|---|---|---|---|---|---|---|
| M | SD | M | SD | M | SD | ||||
| Depression | 19.92 | 11.66 | 28.57 | 12.17 | 17.38 | 11.36 | 7.23 | .00 | .04 |
| Pandemic Stress | 54.54 | 10.89 | 57.07 | 7.72 | 53.38 | 10.83 | 3.24 | .02 | .02 |
| Stressors J | 0.06 | 0.94 | 0.08 | 0.79 | -0.10 | 0.94 | 3.05 | .02 | .02 |
| Reactions | 15.47 | 5.65 | 17.86 | 4.19 | 14.66 | 5.97 | 3.42 | .01 | .02 |
| Strategies | 18.72 | 4.69 | 18.48 | 4.25 | 19.17 | 4.45 | 0.17 | .91 | .00 |
Note. J, M and SD after a Johnson transformation. Bonferroni fit was used.
Discussion
With the objective of analyzing the relationship between Depression and Pandemic Stress, and comparing these variables according to work factors, it can be determined that the work hypothesis was confirmed. It was found that high levels of Pandemic Stress, (i.e.: fear that some relative is infected, hospital consultation, insufficient resources, among others) were associated to high levels of depression symptoms such as hopelessness, pessimism, self-criticism and sadness.
These data coincide with the findings of Shigemura et al. (2020) and Huarcaya-Victoria (2020), who state that the fear of contagion and the uncertainty generated by COVID-19, act as a catalyst for anxiety and depression disorders. From the above, it can be thought that it is not only the fear of contagion that makes people discomfort, but also isolation. In this sense, Macías (2020) explains that the estrangement and demands generated by the pandemic as a whole, may trigger the stress process.
Regarding age, in the present investigation it was found that young people presented higher levels of depression. This result is consistent with previous research by Caccia et al. (2021) who observed that young people tend to have more paranoid thoughts and turn psychological problems into organic and functional symptoms, a fact that decreases as age increases. Likewise, it is vitally important to note that younger people face uncertainty regarding their housing situation and work and professional placement. In Argentina, poverty levels are higher in young adults, which constitutes a factor of vulnerability (Etchevers et al., 2020).
Concerning gender differences, a significant number of research report greater psychological symptoms in people of the female gender over those of the male gender. For example, Johnson et al. (2020) found that women expressed feelings of fear and anguish to a greater extent, along with feelings of responsibility, care, and appreciation of interdependence.
Regarding the above mentioned, women are the ones who are most involved in care tasks, a fact that translates into greater stress considering the number of tasks they perform and the social pressure they receive, this constitutes gender as a risk factor (Mowbray, 2020). Likewise, the economic unemployment generated by the measures around COVID-19 is generating profound socio-economic impacts. The burden of unpaid work in households increased and fell unequally on women, further limiting their time available for productive activities (Actis di Pasquale et al., 2021; Gutiérrez et al., 2020).
Gutiérrez et al. (2020) explain that even before the pandemic, employment indicators showed greater vulnerability in the case of women than in men, finding greater informality, lower wages, lower social protection and greater volatility in the face of fluctuations in the economy. Due to the above mentioned, it is to be expected that women are the ones who perceive themselves to be the most overwhelmed and worried. In addition, teleworking had the effect of accentuating the unequal distribution of household and care tasks. This, in turn, has conditioned the ability of women and men to carry out their work remotely (Actis di Pasquale et al., 2021).
In turn, it is important to mention another possible explanation, and that follows the same line as the previous one, which is gender socialization. This differential socialization links women with the affective, caring and expressing emotions while male gender socialization hinders their expression in certain contexts, the result of heteronormative cultural scripts (Bacigalupe et al., 2020; De Boise & Hearn, 2017). Therefore, it would not only be a greater discomfort but a greater recognition and expression of it.
Likewise, in the present investigation, significant differences were found based on certain labor factors such as the size of the company, the employment situation and the type of work during the Preventive and Compulsory Social Isolation (ASPO). Considering the economic impact of the measures adopted around COVID-19, it was found that those who thought at some point during the quarantine to close their businesses, shops and/or ventures, were those who presented the highest levels of depression. Regarding this, several studies found that the economic decline during the quarantine created serious feelings of anguish and was configured as a risk factor for symptoms of psychological disorders, even several months after the quarantine ended (Desclaux et al., 2017; Mihashi et al., 2009). In this sense, Bericat and Acosta (2020) found that workers experience the uncertainty and vulnerability derived directly from the virus, and those derived from facing their employment situation.
This is evident in another result of the present study, which reflects the discomfort around the employment situation. In other words, it was found that people who are unemployed have higher levels of depression and pandemic stress than employees and the self-employed. This is to be expected if one considers that losing a job means reducing the family income per capita, which can become a traumatic event for both the person and their family nucleus, generating uncertainty, depression, stress, among others (Lozano Chaguay et al., 2020).
The pre-existing Argentine economic crisis is aggravated by the significant economic losses that quarantine implies in the entire population, which increased the vulnerability of the most disadvantaged sectors, who receive the financial impact and the restrictions that it entails with greater force, this being associated with greater symptoms (Barrón & Mayorquín, 2020; Johnson et al., 2020). According to the ILO, work was deeply affected by the pandemic. In addition to being a threat to public health, economic and social disruptions threaten the long-term livelihoods and well-being of millions of people. Consequently, concerns about health and economic issues increase in workers, exposing them to various psychosocial risk factors such as stress and anxiety (Díaz et al., 2020).
In this sense, most workers were forced to change their work modality to Home Office. They are those who, as revealed by this study, have a higher level of pandemic stress than those who kept their work outside home. Malacara (2020) explains that the current context of teleworking generated more stress and forced to extend working hours, especially that of female workers. He assures that, in the beginning, not everyone had the necessary tools to work remotely, and to this is added that the other members of the family are also at home.
This is related to the data collected by the present investigation, in which it was found that those who work within the home are more afraid of being infected than those who work outside the home. In the research by Caccia et al. (2021) found that the greater the consumption of news and the search for information about COVID-19, the higher levels of phobic anxiety, somatizations and paranoid ideation are associated.
Segura (2020) explains that since the pandemic began and due to confinement, the amount of news on the subject, the time that people spent watching television and surfing the Internet, increased considerably. Inaccurate, confusing and even contradictory information brings confusion and fear. In the same line of study, other investigations found that excessive exposure to information about the coronavirus through different media has a negative influence on anxiety, worry and sleep disorders (Gao et al., 2020).
Another result to highlight is the significant differences in employees by company size. It was found that the employees of MSMEs had greater stressors (fear that a family member could have gotten infected, that the health system did not collapse, among others) than the employees of large companies. It is worth mentioning that the employees of MSMEs are the most affected by the demands and measures taken around COVID-19, and it can be hypothesized that it is a factor that enhances stress. For future research, it is suggested to inquire about possible factors that explain this significant difference.
It is important to highlight that the present research has a series of limitations, such as unpaired and non-probabilistic samples. There are much more female subjects in the sample, and the majority completed an undergraduate degree. For future research, it is important to expand the sample of unemployed and men to have more representative samples of each sector since, having a non-probabilistic sampling and unpaired sample groups, the generalization of the results is difficult. Likewise, the criteria used to determine the size of the companies is very limited.
In conclusion, this study showed the importance of investigating the psychological impact generated by COVID-19 on people, considering vital factors such as work and the economy, generating public policies, developing tools and providing resources to deal with the biopsychosocial vicissitudes faced by the world population. At the same time, there is not much research that addresses the problem of micro, small and medium-sized companies, a sector that has clearly been the most economically impacted, so it is encouraged to deepen studies in this population. In the words of Burrow (2020), from the International Trade Union Confederation (ITUC), it is important to think about a post-pandemic world, in which it will be necessary to repair the environment with a more sustainable, safer, and more resistant socio-economic model for all. Agreements reached because of social dialogue between the government, employers 'and workers' organizations will be essential for this transition to be just and promote economic and mental health stability.