Public policies of social isolation during the COVID-19 pandemic substantially altered working conditions. Professionally, thousands of people suffered profound impacts, such as job loss, compulsory vacations, journey and salary reduction, changes to the use of home office, holiday anticipation, changes in appointments, and goal adjustments. All these changes, on top of family impacts and the virus contamination itself, increased work-related stress greatly. Only one study has investigated psychological repercussions and psychiatric symptoms associated with the COVID-19 pandemic in the Chinese workforce (Tan et al., 2020). Of 673 respondents, 10.8% met the diagnostic criteria for post- traumatic stress disorder (PTSD) after returning to work. Besides, 12% revealed moderate to severe concerns about their physical health. In general, low levels of anxiety (3.8%), depression (3.7%), stress (1.5%) and insomnia (2.3%) were found, there were also no significant differences in respect with psychiatric symptomatology amongst workers, technicians, and executives/managers. Stress related to professional activity results in the individual perception of not being able to attend to working demands, which causes psychological suffering, behavior change, negative attitudes towards work and augmented cardiovascular risk (Quick & Henderson, 2016). In this scenario, activities which help mitigate the stress load and offer relief in the toughest moments become essential.
Volunteering is more and more present in the corporate environment (Azevedo, 2007). Companies have developed this kind of program intentionally and motivated by several reasons, as studies by Azevedo (2007) and Fischer and Falcone (2001) show. Besides, they have also started valorizing employees and candidates who have volunteer work experience for available job positions (Cook & Jackson, 2006). Data collected at “Além do Bem”, produced by Santo Caos Consultancy (2017) which involved 828 participants, pointed out that 89% of the interviewed managers from different areas are of the opinion that corporate volunteering makes individuals better professionals, and 62% consider the Volunteering Program as an impactful differential when choosing a job candidate. According to Deloitte Touche Tohmatsu Limited (2016), volunteering can be decisive for getting a new job. Among the managers interviewed, 82% feel more inclined to choose candidates with experience in volunteering, 92% of managers agree that it improves leadership skills and 80% of managers believe that active volunteers move more quickly to leadership positions. In addition to professional benefits and personal development (Loosemore & Bridgeman, 2017; Willems & Dury, 2017), several studies point out the benefits of volunteering for mental health, well-being and, more specifically, as an aid in combating stress (Cavalcante et al., 2015; Leviten-Reid & Campbell, 2016; Musick & Wilson, 2003; Okun et al., 2015; Stukas et al., 2014).
Given this context, this study aims to answer the following research question: Can the practice of volunteering relieve professional stress during the COVID-19 pandemic? The study used the Portuguese version of the job scale produced by Alves et al. (2004) and Hökerberg et al. (2014), for measuring stress and was based on a digitally applied survey.
According to a United Nations report, in 2017 more than 1 billion people were involved in some activity as volunteers (United Nations Volunteers Program, 2018). The theme of volunteering is broad and diverse. From people who are willing to test market products, medicines or surgical procedures, to religious devotees who abandon their work to dedicate themselves entirely to volunteer service, there are different contexts and perspectives for volunteering. An increasing interest in the study of volunteering can be seen in recent decades, and the number of publications dedicated to the topic has grown exponentially (Hustinx et al., 2010).
The concept of volunteering incorporates three key components in its definition: (1) it is an active donation of time and/or skills instead of passive support through monetary donations (Wilson, 2000); (2) it is a planned activity (proactive), to a spontaneous act of helping and serving (Clary & Snyder, 1999); and (3) it often occurs in the context of a voluntary or charitable organization (Wilson & Musick, 1997). Thus, the volunteer is an agent of transformation that works for the benefit of the community. Snyder and Omoto (2008) in a review on the topic of volunteering, defined the term as an aid activity, freely chosen and deliberate, which extends over time and which is often carried out through organizations and on behalf of receptive causes or individuals.
For Cnaan et al. (1996), society’s perception of volunteers can be understood according to four dimensions: (1) free will, (2) remuneration, (3) volunteering formality and (4) who they intend to help. This perception in general considers who is a volunteer according to what are the benefits for the volunteer to perform a certain action, instead of what are the benefits generated for society. In other words, the greater the benefits provided to the volunteer, the lower the perception of society as a volunteer. When it comes to the potential impacts for the volunteer as perceived by co-workers, volunteering deemed to have been done for intrinsic reasons is credited by colleagues and stigmatized when motivated to show others (Rodell & Lynch, 2016).
The growth of volunteering within the corporate environment is increasing and seen as part of a broad agenda to motivate companies to act as committed corporate citizens (Pajo & Lee, 2011). Companies and their employees have long recognized their responsibility for the well-being of communities in which they operate and one of the most common ways to generate impact is by contributing through corporate volunteering (Brockner et al., 2014). According to Moreno and Yoldi (2008) and Herzig (2006), volunteering programs originated in the USA in the 1970s and since the 1990s have become common in British organizations, and in European organizations, especially in Holland, Switzerland and Germany. Among the benefits for volunteers, there is the possibility of relationship between volunteering and loyalty to the organization. Brockner et al. (2014) concluded that volunteering is positively correlated related with the volunteer’s commitment to the organization, and that the experience of personal integrity in the work environment is responsible for this correlation.
For Rodell and Lynch (2016) the effects of the relationship between volunteering and the work of a certain individual are mutual, considering that the work experience is one of the factors that drive volunteering, especially in situations where the individual does not perceive their work activity as important for his life. In addition, volunteering does not interfere with the individual’s work, on the contrary, there is a positive indirect relationship in performance because the activities complement each other.
Based on the literature on this matter, Loosemore and Bridgeman (2017) affirm that companies can also benefit significantly from corporate volunteering programs. Pago and Lee (2011), through a questionnaire and focus group, attempted to comprehend, in the employees’ perceptions, the unfolding of the participation of the voluntary initiative sponsored by the company. Findings highlighted the importance of the humanitarian concerns as a key factor to involve employees in initiatives sponsored by the companies. Still, according to the authors, being a volunteer provides a counterpoint to recent academic contributions that have underestimated humanitarian “motivations” or underestimated their potential intrinsic potential motivating benefits for volunteering employees. These include: feelings of altruism (satisfaction of the desire to help and reciprocate); meaning (making an interesting impact); organizational citizenship (helping the company to present a positive image of the community); variety of roles (opportunity to do something other than normal work); relational (creating new social connections); networking opportunities (new relationships); and personal benefits (as an opportunity to build your own reputation) (Pajo & Lee, 2011).
Among the most studied topics in volunteering, motivations and benefits are the most frequent (Chacón, Gutiérrez, Sauto, Vecina, & Pérez, 2017). Although they are two distinct themes, studying them separately would be complex, since the search to understand people’s motivations to get involved in volunteering involves understanding the perceived benefits.
According to Gerstein, Wilkeson & Anderson (2004), the motivation for volunteering differs when it comes to gender issues. The authors found that male individuals reported that they perceive benefits in these activities. The motivation of female individuals in general is not associated with the benefits resulting from volunteering. Despite recognizing them, female individuals reported motivations associated with selfishness.
Regarding the volunteer’s age aspect, Van Willigen (2000) argues that there are also differences in motivations and meanings for the volunteer’s life. Over time, adult and older individuals experience greater satisfaction in their lives by getting involved in volunteering, as well as in the perception of improved health than younger adults. For the author, this difference may be related to the type of volunteer work, which differs per age group.
Beyond benefits for individuals, for companies, there is a possibility of a relationship between volunteering and loyalty to the organization.
Dennis, Scanlon and Sellon (2017) argue that several studies have highlighted aspects and subjective values that influence development, engagement, and willingness to volunteer. For the authors, religious beliefs and values, such as altruism, the desire to repay and help the needy, are also pointed out as reasons for participating in activities of this nature. In this same sense, Garland, Myers and Wolfer (2008) point out that there is a direct relationship between volunteering and spiritual beliefs and values. For the authors, volunteers who are religious can perform community service more motivated and more effectively. The study by Garland, Myers and Wolfer (2008) was carried out with 7,405 people and highlights that a great motivation for volunteering is that it provides a way for participants to share their faith.
Johnston (2013) evidenced that the involvement of spiritualized individuals acts, in fact, as a feeding mechanism for targeting a variety of volunteer activities over time. Another aspect highlighted by the author is that people most involved in volunteering at religious institutions are much more likely to engage in volunteer efforts with other voluntary organizations without religious identities.
Einolf (2011) explains that religions, values, ideas, and language are not merely psychological phenomena, but also social facts, as people learn religious principles from other people and internalize them in their own census of identity. They resort to these ideas to engage in social behaviors and use language to build stories that explain why they help others and what helping others means to them. According to Einolf (2011), taking ideas and language seriously allows for a broader and more accurate understanding of the connection between religion and helping others.
Einolf (2011) pointed out that quantitative studies demonstrated that religiosity was not a strong predictor of volunteering. Thus, he undertook an empirical study, which included 88 narrative in-depth interviews. One of the most interesting findings of this study was that subjective religiosity had the strongest relationship with wellbeing support when considering involvement in multiple prosocial behaviors. People who volunteered and donated financially to secular religious charities were significantly more likely volunteer than less engaged people.
Several studies have sought to develop ways to measure and identify motivations for volunteering. Bales (1996) developed the Volunteer-Activism Scale. He created a Likert-like scale, composed of 20 items. In the empirical analyses, Bales (1996) worked with a sample of 1290 participants and identified four dimensions for measuring the motivations: i) Feeling of effectiveness; ii) Sociability; iii) Idealism or philosophical commitment and iv) Feeling good. The use of this scale makes it possible to deduce which individuals are more likely and those who are less likely to be volunteers in charitable actions.
Nickell (1988) also developed an assessment scale, the so-called Aid Attitudes Scale, whose aim was to analyze beliefs, feelings and behaviors to measure positive and negative attitudes towards helping others. In this research, 408 undergraduate students participated in four different studies to assess psychometric properties of the developed scale. The contribution of this study lies in offering a valid and reliable measure of helping attitudes. The research included a gender issue, and one of the findings of the study was that women have a more positive attitude towards contributing to volunteering.
Volunteering benefits are not often studied in scientific studies. To analyze main findings of scientific articles related to the topic, a research on Web of Science, using the term “benefits of volunt*”, was done. Thirty-two articles were associated with corporate or professional studies, in which can be grouped in four categories by similar subjects: i) Satisfaction of Personal Values, Altruism, Meaning and Belonging; ii) Development of Social Relations, Integration with Society, making new friends; iii) Personal, professional development and acquisition of new skills; iv) Personal well-being, physical and emotional health and longevity. Table 1 shows the distribution of studies between the groups.
Table 1 Studies on Volunteering benefits distributed on groups
Note. Source: Lopes, 2020.
Professional Stress Measures
Occupational stress results in the individual’s perception of not being able to attend work demands, which causes psychic suffering, behavior changes, negative attitudes towards work and augmented cardiovascular risk (Quick & Henderson, 2016). In 1979, Karasek found that workers whose work was classified as highly demanding and over which they have low control (measured by the decision latitude) reported significantly more work exhaustion. In the demand-control model, psychological demands are measured according to issues such as speed, intensity, effort, and conflict of demands at work, while control is measured by decision latitude, through issues such as learning, skill level, initiative and repetition of tasks, as well as decision-making authority on what to do and how to work (Chungkham et al., 2013; Hökerberg et al., 2014;).
The model also allows a classification of the work from the crossing of the magnitude of the dimensions, psychological demand and control (Karasek, 1979), namely: active type – characterized by high demand and high control; passive type – marked by low demand and low control; high demand – characterized by high demand and low control; and finally, low demand, resulting from the combination of low demand and high control. From this approach, that focuses on the assessment of the risk of occupational stress on the way work is organized, the repercussions of changes in the organization of work as a result of an event, such as COVID-19, can be investigated.
The processes of restructuring and management of professional activities due to the pandemic have led to significant changes in the organization and management of work. The International Labour Organization (ILO, 2020) monitoring studies on the impact of the COVID-19 pandemic on the work environment, report until march 2020, four out of five people (81%) in the 3.3 billion global workforce are affected by the total or partial closure of the workplace, with an estimated reduction of around 6.7% in the working day, which is equivalent to 195 million full-time workers. In addition, estimates from Global Workplace Analytics (2020) indicate that 25 to 30% of the workforce will be working from home several days a week by the end of 2021 because of COVID-19’s influence.
Currently, there is little information about how changes in the work environment due to the pandemic can impact workers from different sectors, beyond the health sphere (Tan et al., 2020).
Method
This research makes use of theoretical framework and data analysis from field research to meet its objectives. As a research project, it can be classified as an applied research, as, according to Roesch (2013, p. 62), this genre of research aims to “understand the nature and source of human problems, addressing issues considered important by society”. This concept fits the research, since it aims to analyze a relevant and current issue to individual’s development and organizations.
Participants
The survey was applied online, making use of Microsoft forms, as this tool allows several graphs analysis, and it exports all data obtained from the respondents to a unique Excel file, in an organized manner. The link, which was broadly disclosed on social media and email, was available to the respondents from May 21st 2020 to May 28th 2020, totalizing 996 respondents. It is important to mention that participants were chosen randomly and conveniently.
Instrument
The questionnaire included demographic and socioeconomic questions, aiming to determine the profile of the sample and also to analyze these factors in the respondents’ perception. To measure participation in volunteering, respondents were asked:
Regarding your volunteering practice in respect to COVID-19:
A. I did not practice volunteering before, and I am not practicing now.
B. I started volunteering due to the COVID-19 pandemic.
C. I already volunteered before and I continue volunteering now.
D. I used to volunteer before, but I have not been volunteering lately.
E. I volunteer during fewer hours during the COVID-19 pandemic.
Assertions were also chosen to measure the respondents’ stress level, based on the demand and control questions of the reduced version of the Job Stress Scale adapted to the Brazilian context (Alves et al., 2004; Hökerberg et al., 2014), in addition to some questions about measures taken related to COVID-19. Table 2 shows the list of statements and the associated variables.
Table 2 Assertions to measure opinion about working home office
Assertive | Variable | Classification |
---|---|---|
I have difficulty defining my role and functions at home | D. Function | Dependent |
I have to do work tasks very quickly | Quickly | Independent |
I have to produce a lot and in a short time | Shorttime | Independent |
Work demands too much | Demands | Independent |
I have enough time to complete the work tasks | EnoughTime | Independent |
My work often has contradictory or disagreeing requirements | Contradict | Independent |
I have the possibility to learn new things in my work | Learning | Independent |
My job requires a lot of skill or specialized knowledge | Habilcon | Independent |
My job requires me to take initiatives | Iniciatives | Independent |
In my work, I have to repeat the same tasks many times | Repeat | Independent |
I can choose HOW to do my job | Howtodo | Independent |
I can choose WHAT to do in my work | Whattodo | Independent |
My organization offers me psychological support for situations faced during COVID-19 | Psychological Support | Independent |
My organization has been understandable with my difficulties and particularities during COVID-19 | Comp | Independent |
My organization took clear steps to confront COVID-19 | COVID-19 Measures | Independent |
Data Collection Procedures and Ethical Considerations
To measure the volunteering relations to the professional stress, two variables were established as dependent ones. Stress variable was created with the sum of the assertions related to the job scale. The variable D.Function was determined from the statement: “I have difficulty defining my role and functions at home”. We asserted the capacity of defining one’srole and function is related to professional development, maturity at work and has important role on the emotional stability of the individuals, contributing to the reduction of professional stress.
In order to verify the study quantitatively, a Multiple Linear Regression model was developed, rotated once for each dependent variable, as shown below:
Namely:
E(Y│X) – Dependent variable
β0 – Constant
β1 to β13 – Independent variables: Id (Age), S (Sex), EC (Marital Status), GI (Education level), EP (Professional Experience), PE (Company size), LD (Leader), CV (Continued Volunteering), APP (Psychological Support), MCO (COVID-19 Measures), Comp (Understandable), RD (Income).
e – Error term
After collection and previous analysis, the data were organized and standardized in Excel, the variables were properly adjusted and coded, finally, all data were handled in Software Stata version 15.0, generating the descriptive statistics and the remainder of the multiple linear regression, which will be presented and discussed in the next session.
After collection and previous analysis, the data were organized and standardized in Excel, the variables were properly adjusted and coded, finally, all data were handled in Software Stata version 15.0, generating the descriptive statistics and the remainder of the multiple linear regression, which will be presented and discussed in the next session.
Results and Discussion
The data analysis sought to study the demographic characterization of the sample and the respondents’ opinions, subsequently, to explore the data in the multivariate analysis. Table 3 provides a summary of the descriptive statistics.
Table 3 Summarizes Descriptive Statistics
Variables | Observations → n | 996 (100%) |
---|---|---|
Average Ages | 39 years old | |
Women | 66% | |
Married | 56% | |
Has School Children | 36% | |
Occupies leadership role | 37% |
Income, Education level and Professional experience variables were measured by a scale created to this study, and the mode was calculated. Most respondents’ income was between R$ 3,601 and R$ 6,000.00. The education level of the sample is a prominent factor. The Mode was in 5, Complete Higher Education. In general, 75.78% have completed higher education or higher levels, in particular, 28.56% have stricto sensu. As for the item referring to professional experience, the Mode of the scale points to 4, above 5 years. In the percentage distribution, 80.15% of the participants have more than 5 years of experience.
Concerning the beginning of home office activities 10% of the respondents had already worked in this modality before the social isolation, 77% started after COVID-19 crisis and they have been working for over a month, 11% two weeks ago and 2% had only started the activities a week before answering the survey. Considering the social and economic impacts of COVID-19, 4% of the sample lost their jobs. Some organizations have opted for salary reduction policies. Among respondents, 22.17% had some kind of reduction in their income due to the impact of the pandemic crisis of COVID-19, with or without reduced working hours.
Concerning volunteering, 38.47% of respondents have never volunteered before. 54.08% of this research respondents volunteered before COVID-19, 16.60% stopped volunteering during the pandemic; 13.12% completely interrupted the activities; and 24.35% continued their participation in projects as usual. An interesting detail lies in 7.46% of the respondents, who started volunteering in the pandemic outbreak.
Multivariate Analysis
The data were standardized, coded and run on Stata IC v.15. The validation tests for multiple linear regression were run and considered satisfactory. Table 4 shows the results obtained.
Table 4 Multiple linear regression results
Variables | Function Delimitation | Stress |
---|---|---|
Age | 0,0116** | -0,0322* |
Women | -0,0061 | 0,0751 |
Married | 0,0322 | -0,2541 |
Has school-age children | -0,2184** | -0,3719 |
Degree of Education | -0,0528 | -0,0866 |
Professional experience | 0,0585 | -0,1110 |
Company size | -0,0344 | 0,5350*** |
Occupies Leadership Position | -0,1066 | -0,2716 |
Continues Volunteering at COVID | 0,2454** | -0,8522*** |
Psychological Support at COVID | 0,1084* | -0,3453 |
Business Measures in COVID | -0,0263 | -1,1887*** |
Understanding COVID Limitations | 0,2111 | -1,3186*** |
Income | 0,0521 | -0,1232 |
_cons | 2,6112 | 33,6563 |
N | 367 | 638 |
R2 | 0,068 | 0,255 |
Prob > f | 0,002 | 0,000 |
Note. * Statistically significant at 10%; ** Statistically significant at 5%; *** Statistically significant at 1%.
The last three lines of Table 4 present validation factors for the equation used. R2 measures the model’s explanatory capacity, that is, how much the independent variables X explain the Y variation, the dependent variable (Fávero et al., 2009). R2 can range from 0 to 1 (from 0 to 100%). In the models studied, the R2 found were between 6.8% and 25.5%, which means that each model explains this percentage of the dependent variables. The number found is sufficient for the research, considering that many other factors not listed in these equations can contribute to stress and the ability to limit its function. The indicator found can be considered low to moderate, considering that Green (1999) considered that an R2 of 0.5 is relatively high. It is worth mentioning that R2 should not have an exaggerated weight in econometric models, in addition to being subject to much discussion between different authors (Fávero et al., 2009). For Gujarati (2003), R2 has a very modest role in the regression analysis, being a measure of the quality of the fit of a sample. Therefore, a high R2 is not evidence in favor of the model and a low R2 is not evidence against it. The Prob > F indicator measures the significance of the model as a whole, the closer to 0 the better. The N of the sample varies according to each model because the form applied contained an option “I have no opinion” in each statement, for the framing of respondents who did not feel able to classify the statement. These responses were disregarded when calculating the regression.
The respondent’s perception concerning his capacity of clearly defining roles and function in the home environment were measured in the first model. Age was relevant statistically, pointing out that the older the respondent, the greater his perception that he can define his functions at home more properly. Having kids was relevant, but negatively. Defining roles and function in the home environment is usually challenging while working from home. Some factors in this study predict the ability of workers to better adjust to this type of professional activity. These factors include: age, being a psychologist and receiving psychological support during COVID-19. Identifying these factors is essential, as there is no consensus in the literature whether the home office brings greater balance between work and family. Some studies point to balance (Gajendran & Harrison, 2007), while others to conflict (Kossek et al., 2006). A previous study that analyzed the work-family conflict for different age groups showed that the conflict is greater among younger people, who reported insufficient time for work-related tasks due to family demands. Older workers reported a greater participation of the partner in domestic tasks, comparing the lower proportion in the younger age groups (Donders et al., 2012).
Being a volunteer and receiving psychological support during COVID-19 increased the respondents’ perception that they define their roles and functions properly when working from home. This finding can contribute to professional stress, since the ability to define professional roles is associated with full control of activity at work and in personal life. This finding strengthens the concept that volunteering plays an important role in both personal and professional development of individuals. The contribution of volunteering to professional maturity and skills development has been verified by several studies, such as Leviten-Reid and Campbell (2016), Loosemore and Bridgeman (2017), Lopes Jr. et al. (2018), Lopes Jr. (2020) and Willems and Dury (2017).
The second model analyzed professional stress during the pandemic. The only statistically significant and positive variable was the company size, that is, the larger the company, the greater the professional stress of the respondent. It is well known that large companies, in general, have systems focused on goals and present greater pressure for results, which may contribute to greater stress levels at work. In addition, the fear of mass layoffs in large corporations might have also influenced this relationship with professional stress. The other relevant variables were negative: Age, Continue Volunteering, COVID-19 measures taken by the company and Comprehension during the pandemic. The presence of these items reduces the respondents’ professional stress.
Age wise, findings point that the older the respondents, the greater his ability to handle work pressures, that is why it shows less stress levels. This item can also be related to the individuals’ maturity. With longer life and experience, people tend to handle frustrations and professional pressures better. The results obtained by the variables related to support offered by organizations during the COVID-19 crisis were expected, since these measures leave employees with the feeling of more security and support form by their companies.
The continuity of volunteering, which is the focus of this research, was negatively relevant, serving as a mitigation for professional stress. The relationship of volunteering with health and wellness benefits has been highlighted in several studies (Cavalcante et al., 2015; Cnaan et al. 1996; Daoud et al., 2010; Gallarza et al., 2013; Kasteng et al., 2004; Kwok et al., 2013; Haski-Leventhal & Bargal (2008), 2008; Leventhal et al., 2018; Leviten-Reid & Campbell, 2016; Morrow-Howell et al., 2009; Musick & Wilson, 2003; Okun et al., 2015; Parkinson et al., 2010; Pushkar et al., 2002; Stukas et al., 2014; Tang et al., 2010; Thoits & Hewitt, 2001; Van Willigen, 2000). It is worth noting that this variable was related to the continuity of the practice of volunteering, that is, people who practiced volunteering and continued to practice even after the social isolation caused by COVID-19. The contribution of this variable to reducing professional stress may be associated, to volunteering itself, with the continuity of an important routine for the respondents’ purposes, as a stress reducing factor in the respondents’ lives.
Conclusion
Changes that occurred in the corporate environment during the pandemic demonstrate that people were not prepared to deal with this new work environment. Several researches have been developed in an attempt to better comprehend these sudden changes on the organizational environment and employees’ health and well-being.
This article sought to analyze the relationship between volunteering and professional stress in the context of limitations imposed by COVID-19. This study was developed out of two variables, related to role and function definitions and professional stress, obtained by the combination of variables to assess demand and control at work. In addition to other relevant variables discussed in the results section, the variable which refers to volunteering continuity, the focus of this study, was relevant statistically in both models, that is, having continued volunteering during the isolation provoked by COVID-19 increases the respondents’ perception of being capable of defining their roles and functions working from home, and it decreases perceptions of professional stress.
In a world with so many uncertainties, this research can be a great stimulus to the concept of humanity. Even if there are cases of selfishness, exploitation, and even corruption in search of advantages in this delicate moment, realizing that those who are concerned with doing good and contributing to society, are also benefited, can be an incentive for those who have not yet adopted volunteering. The study contributed to at least three spheres: Nonprofit organizations, offering arguments for the recruitment, retention, motivation and engagement of volunteers; Companies, demonstrating that investments in corporate social responsibility and corporate volunteering can bring benefits to their employees and consequently bring organizational well-being; and, finally, for individuals, proving that their effort in favor of building a better world can also bring mental health and a better emotional balance in the face of professional demands.