The Relationship Between Occupational Stress, Burnout, and Perceived Performance: The Moderating Role of Work Regime

Abstract

Globalization, digital transformation, and organizational changes have led to significant transformations in the world of work, substantially increasing workloads, which can result in high levels of stress and burnout among employees. The main objective of this study was to investigate the association between occupational stress and perceived performance and whether this relationship was mediated by burnout. In addition, we sought to understand whether the work regime (in-person, hybrid, and remote) moderates the relationship between occupational stress and burnout. The sample for this study consisted of 325 participants working in organizations based in Portugal. The data collection procedure was non-probabilistic, intentional, and snowball-type. This is an exploratory, correlational, and cross-sectional study. The results indicate that only the dimension ‘stress with users’ has a negative and significant association with performance. On the other hand, the dimension ‘stress with career and remuneration’ has a positive and significant association with performance. The dimensions ‘stress with users’ and ‘stress with workload’ have a positive and significant association with performance. Only ‘stress with workload’ has a positive and significant association with exhaustion. Distancing has a total mediating effect on the relationship between stress with users and perceived performance. The work regime has a significant effect on distancing. The work regime moderates the relationship between ‘stress with working’ conditions and exhaustion. Given the current work regimes, especially after the COVID-19 pandemic, it can be concluded that, among the dimensions of occupational stress, the most critical is stress with working conditions.

1. Introduction

Mental health is the foundation of well-being and quality of life for everyone, enabling us to maintain a balance between our cognitive and emotional levels (Hammoudi Halat et al., 2023). According to the World Health Organization (WHO, 2022), it can be defined as a state of mental well-being that allows individuals to cope with stress, make use of their abilities, learn, and work efficiently. The WHO (2022) considers mental health to be a fundamental right.

Globalization, digital transformation, and organizational changes have had a profound impact, leading to significant transformations in the world of work. Authors Maslach and Leiter (2016) argue that these transformations have led to a substantial increase in workload, daily demands, and competitiveness, resulting in high levels of stress and burnout among employees. Work-related stress is defined as a state of tension resulting from the disparity between the demands of work and the resources available to deal with them (Jiang et al., 2022). It has been a widely discussed topic due to its negative consequences for employee well-being, resulting in physical, psychological, social, personal, and professional impacts on the individual (Freitas et al., 2023; Santos et al., 2018). In Portugal, the cost of problems related to stress and mental health among employees is very high for organizations, with the Ordem dos Psicólogos Portugueses (2023) estimating that these costs reached €5.3 billion in 2022. These losses are caused by absenteeism, presenteeism, and a decline in productivity, as occupational stress has a negative and significant association with employees’ mental health and performance (Chen et al., 2022).

Freudenberger (1974) introduced the concept of burnout, which was later developed by Maslach and Jackson (1981). This concept refers to a state of emotional exhaustion, depersonalization, and reduced personal and individual fulfilment at work. W. B. Schaufeli et al. (2009) associate this process with various organizational factors, including work schedule, workload, and working conditions. Burnout negatively impacts not only the well-being of employees but also their perceived performance, motivation, productivity, and turnover intentions (Demerouti et al., 2001; Freitas et al., 2023). The relationship between occupational stress, burnout, and performance can be understood in the context of the job demands-resources model, developed by Demerouti et al. (2001). According to these authors, the model consists of two main categories: job demands and job resources. These two categories are related to the two dimensions of burnout proposed by the Oldenburg Burnout Inventory, developed by Demerouti and Nachreiner (1998). Job demands are related to the exhaustion component, and job resources are related to disengagement. High demands and scarce resources can lead to adverse outcomes for both the individual (mental and physical health problems) and the organization (low performance) (W. B. Schaufeli, 2017). It has been added to the list of references.

One factor that can be identified as a determinant in the perception of occupational stress and burnout is the work regime, which can vary between face-to-face, hybrid, or remote work arrangements. Tavares (2017) and Wang et al. (2021) suggest that teleworking can reduce specific sources of stress, such as daily commuting and constant interruptions; however, it can also contribute to increased social isolation and difficulty in maintaining a work–life balance. According to Bakker and Demerouti (2017), the interconnection of these concepts and their impact on employee performance have been the subject of considerable attention in the scientific literature, given their importance and relevance to business effectiveness and employee satisfaction.

Given this context, the primary objective is to investigate the relationship between occupational stress, burnout, perceived performance, and work regimes (face-to-face, hybrid, and remote) to understand how these factors interact and their impact on both employees and organizations. The main objective of this study is to examine the relationship between occupational stress and perceived performance and whether burnout is the mechanism that explains this relationship. Another objective is to study the moderating effect of the work regime on the relationship between occupational stress and burnout.

This study aims to provide insights into the most critical dimensions of occupational stress, enabling organizations to create conditions that reduce employees’ occupational stress levels and enhance their performance. It is also intended to highlight the importance of integrating the principles of Resource Conservation theory (Hobfoll, 1989) and Job Demands-Resources theory (Demerouti et al., 2001) into Human Resource Management practices to create environments that promote the success of employees and the organization in the face of constantly evolving professional challenges. The loss of resources outweighs the benefits, and to address this, it is necessary to invest in and protect them, thereby preventing loss and recovering benefits (Hopkins & Bardoel, 2023). From the perspective of Hobfoll and Freedy (2017), in challenging work environments, when job demands are high, resources become essential to prevent burnout. Additionally, there are currently different work regimes in place. According to Demerouti and Bakker (2023), organizations should consider the side effects related to new types of demands and resources associated with new work regimes. This study aims to provide organizations with guidance on these new types of demands and resources.

2. Theoretical Framework

2.1. Occupational Stress

The origin and meaning of the word “stress” have undergone some changes since the 14th century. The definition of work-related stress may vary, but in general, it refers to a negative physical, mental, or emotional response that arises when the demands of the work environment exceed the worker’s capacity or resources.

Abrahão and Cruz (2008) state that stress is a way of facing reality, and its expression reflects the discomfort that people experience. Lazarus and Folkman (1984) argue that occupational stress is a process that occurs when the demands of work exceed the resources available to individuals to cope with them. Stress can arise as a physical or psychological response to moments of increased tension or difficulty (Selye, 1976). Karasek and Theorell (1990) state that occupational stress arises when daily responsibilities and pressures are combined with a lack of autonomy and decision-making power. Cooper and Marshall (1976) believe that occupational stress can be defined as a negative interaction between employees and their work environment, caused by excessive demands and a lack of ability to meet them effectively and efficiently. The WHO (1986) defines this concept as a physical and emotional reaction that occurs when work requirements do not align with the abilities or needs of employees, thereby jeopardizing their physical and mental health. For Bicho and Pereira (2007), occupational stress, as an emotional state, has become one of the most significant mental health problems affecting the working population. When occupational stress becomes chronic, its consequences, both personally and professionally, can be both physical and psychological (Yao et al., 2019).

Many factors contribute to work-related stress:

(a)

Meeting short deadlines can lead to employee overload (Hirschle & Gondim, 2020);

(b)

Lack of autonomy increases levels of frustration and stress (Lazarus & Folkman, 1984);

(c)

Conflict between coworkers can generate high levels of tension (Maslach & Leiter, 2016);

(d)

Poor working conditions lead to dissatisfaction and increased stress (Souto et al., 2021);

(e)

Lack of motivation and professional recognition can lead to frustration (Cooper & Cartwright, 1994);

(f)

Resistance to organizational change can generate high levels of stress (Hirschle & Gondim, 2020).

In addition to the negative consequences at the psychological level and on employee performance, occupational stress can lead to cardiovascular disease, headaches, and insomnia (Oliveira & Paula, 2021), anxiety, depression, and burnout (Maslach & Leiter, 2016), decreased productivity and increased errors (Cooper & Cartwright, 1994), and social isolation and interpersonal conflicts (Souto et al., 2021).

In conclusion, workplace stress is a complex process that affects both employees and companies, making it essential to recognize its causes and implement effective strategies to promote well-being and balance.

2.2. Perceived Performance

Employee performance is a crucial and significant aspect of a company’s success, as it has a direct impact on productivity and competitiveness (Chiavenato, 2014; Robbins & Judge, 2013).

The concept of performance can vary, but it is generally related to the ability to achieve established goals and desired results efficiently and effectively. According to Chiavenato (2014), performance refers to the behavior that employees exhibit in the performance of their activities, considering the established goals and the efforts applied to achieve them.

For Robbins and Judge (2013), performance relates to how people contribute to the success of companies in terms of achieving established goals, productivity, and work quality levels. In this way, it is linked to the efficiency and effectiveness with which people work to achieve the goals set. Drucker (1999) argues that performance can be defined because of actions, and that it is therefore crucial to perform tasks assertively in order to create value for the company and achieve organizational objectives. Workers control this behavior, and everyone’s contribution can be evaluated based on the quality, quantity, and importance of the results (Bernardin & Russell, 2013).

For Drucker (1999), it is essential that companies develop effective management strategies (competence development and definition of clear objectives aligned with the company’s strategy), and Kaplan and Norton (1996) believe that it is essential to create tools that contribute to improving employee productivity and ensuring sustainable performance.

It is essential to emphasize that employee performance is not solely dependent on the individual, but also reflects the company’s culture, leadership, and opportunities. It is essential to invest in employee performance to enhance individual development and drive the growth and success of companies in the market (Chiavenato, 2014).

In this study, we will use perceived performance as a construct. Molina-Azorín et al. (2009) consider perceived performance to be a subjective measure that helps us assess performance.

Occupational Stress and Perceived Performance

Stress in the workplace can have a profound and significant impact on employee performance, influencing both individual and organizational factors.

According to Selye (1974), frequent and continuous exposure to stress can lead to burnout syndrome, resulting in decreased performance and productivity. Anxiety, fatigue, and low levels of performance are caused by work-related stress (Lazarus & Folkman, 1984).

Occupational stress impairs employee performance by decreasing concentration, reducing efficiency, increasing the number of errors, and lowering the quality of work performed, as well as leading to physical and psychological health problems. Another factor that impairs performance is the deterioration of relationships with coworkers, as the adoption of more aggressive and inappropriate behaviors hinders effective communication and reduces team spirit.

A study by Chen et al. (2022) found a negative and significant association between occupational stress and performance. Zhao et al. (2023) conducted a study with employees in the civil aviation sector, concluding that there is a significant negative association between the occupational stress experienced by Chinese civil aviation pilots and their mental health, performance, and job satisfaction. Ari (2025), in a study conducted with healthcare professionals, also concluded that occupational stress has a negative and significant association with performance.

In conclusion, occupational stress has a direct impact on how employees perform their duties, and it is possible to understand how it affects their organizational performance. This relationship can be explained by the Job Demands-Resources theory developed by Demerouti et al. (2001) and by the Conservation of Resources Theory developed by Hobfoll (1989). These two theories explain how occupational stress can influence performance. When demands are high and resources are scarce, outcomes such as performance are negatively affected (W. B. Schaufeli, 2017). Another theory that can explain this relationship is the stress-performance model, also known as the Yerkes–Dodson law, developed by Yerkes and Dodson (1908). According to this model, stress can have positive and negative effects on performance, depending on the level of stress. Both employees and organizations must know how to manage stress to maximize performance, recognizing that the appropriate degree of stress varies from one individual to another and from one activity or situation to another. Thus, the first hypothesis to be studied based on these two variables is presented below:

Hypothesis 1.

Occupational stress has a significant negative effect on perceived performance.

2.3. Burnout

Freudenberger (1970) was the first to introduce the concept of burnout, defining it as a state of physical and mental exhaustion resulting from excessive involvement with work demands. According to Maslach and Jackson (1981), burnout can be characterized as a state of psychological fatigue, characterized by a lack of energy and overload, the adoption of negative attitudes toward work, and reduced personal and professional fulfilment. Similarly, W. B. Schaufeli and Enzmann (1998) state that excessive and recurring stress in the workplace causes this emotional disorder. The WHO (2019) includes burnout syndrome in the International Classification of Diseases (ICD-11), arguing that this process stems from occupational stress that has not been managed successfully and effectively. When work demands are intense and cause significant pressure, people struggle to adapt to such changes and often experience professional exhaustion (Maslach & Leiter, 2016).

Burnout can arise due to several factors, such as excessive workload or unrealistic deadlines (Hirschle & Gondim, 2020), little autonomy in decision-making or in how work is managed (Lazarus & Folkman, 1984), a conflictual work environment or lack of professional recognition (Cooper & Cartwright, 1994), excessive working hours without time to rest or be with family or friends (Maslach & Leiter, 2016), and instability and insecurity about not being able to achieve expected goals (Hirschle & Gondim, 2020).

Burnout can have serious consequences for employees as it leads to mental health problems (depression and anxiety) and physical health problems (hypertension, cardiovascular disease, diabetes) (Maslach & Leiter, 2016). However, companies are also affected by the onset of this syndrome, namely with a damaged work environment, decreased productivity, increased absenteeism and turnover, high costs, loss of talent, and a higher percentage of errors (Cooper & Cartwright, 1994).

Similarly, it is also important for employees to adopt strategies to better manage stress, such as setting boundaries between their personal and professional lives, exercising regularly, maintaining a strong support network, and seeking help if they begin to experience signs of exhaustion and burnout (Lazarus & Folkman, 1984). In conclusion, burnout is a significant health issue that impacts both the performance and quality of life of employees. For this reason, it is essential to learn to recognize the signs and practice preventive measures to reduce or avoid the impact that this condition has on people and companies.

2.3.1. Occupational Stress and Burnout

Workplace stress is a primary contributor to burnout. The relationship between occupational stress and burnout can be explained by mechanisms such as prolonged exposure to stress where people find it difficult to cope with the demands of everyday life over a long period, frequent overtime or overly complex tasks (Hirschle & Gondim, 2020), the perception of not having control and autonomy when making decisions (Lazarus & Folkman, 1984), conflicts in the workplace and lack of professional appreciation and recognition (Cooper & Cartwright, 1994), financial instability (Hirschle & Gondim, 2020), and lack of time to rest and engage in leisure activities (Maslach & Leiter, 2016).

Occupational stress can increase burnout to the extent that constant pressure to meet deadlines and achieve expected goals, a lack of autonomy, frustration, and a lack of recognition can lead to extreme fatigue, a high level of demotivation, and carelessness. All these factors aggravate the initial symptoms and accelerate the progression to a state of exhaustion (Maslach & Leiter, 2016; Lazarus & Folkman, 1984; Freudenberger, 1974). In a study conducted by Freitas et al. (2023), which involved Portuguese tax and customs inspectors as participants, these authors concluded that there is a positive and significant association between occupational stress and burnout levels. This relationship can be interpreted considering Job Demands-Resources Theory, developed by Demerouti et al. (2001), which posits that high job demands lead to higher levels of exhaustion and low job resources lead to higher levels of disengagement. This reasoning led us to formulate the following hypothesis:

Hypothesis 2.

Occupational stress has a positive and significant effect on burnout levels.

2.3.2. Burnout and Perceived Performance

Burnout has a profound impact on employee performance and the organizational environment. Burnout causes reduced productivity and decreases decision-making ability (Maslach & Leiter, 2016). Employees experiencing burnout are unable to focus, resulting in delays, frequent errors, a decreased ability to perform tasks correctly, and lower work quality. In addition, these authors argue that employees with this emotional disorder have difficulty processing information in a clear, coherent, and objective manner, causing them to make hasty and impulsive decisions.

Burnout is a condition that harms the health and quality of life of employees, as well as the results and objectives set by organizations. Therefore, it is essential to implement strategies that ensure balance and success in the workplace. According to Freire Palacios et al. (2024), a significant negative association exists between burnout and performance. Lei et al. (2025) also found a significant negative association between burnout and performance. The mechanism that leads to burnout and explains low performance levels can be explained by the Conservation of Resources Theory, developed by Hobfoll (1989). Burnout can occur when there is a loss of resources. Employees tend to protect their resources and acquire new ones because if they lose them or the demands exceed their resources, they become exhausted, demotivated, and less effective, which is associated with low performance levels (Harris et al., 2009; Hobfoll, 2001). The following hypothesis is therefore formulated:

Hypothesis 3.

Burnout has a significant negative effect on perceived performance.

2.3.3. Occupational Stress, Burnout and Perceived Performance

Burnout emerges as a reaction to occupational stress and intensifies feelings of tiredness, reducing energy, the ability to maintain focus and concentration, and consequently performance levels (Maslach & Leiter, 2016). Bakker and Demerouti (2017) state that excessive work demands and insufficient resources to manage them lead to increased exhaustion and a decline in performance levels. They also note that burnout acts as an intermediary in this relationship, reducing employee motivation and commitment. Taris (2006) argues that burnout is linked to a decrease in productivity and quality at work, as more tired employees are unable to focus and exhibit the same reasoning and decision-making abilities. Thus, it can be concluded that burnout, resulting from Occupational stress, decreases job satisfaction, causing employees to exhibit less initiative and proactivity, which in turn affects organizational performance (W. B. Schaufeli et al., 2009).

Occupational stress contributes to the onset of burnout syndrome, which in turn aggravates the effects of stress on perceived performance. This process can be continuous, which hinders and delays the recovery of workers (Maslach & Leiter, 2016).

Given that employees are more susceptible to mental and emotional fatigue, burnout undermines the relationship between stress and performance, leading to reduced productivity, increased turnover, and a negative impact on company performance. In a study conducted by Chen et al. (2022), mental health (specifically, burnout) mediates the relationship between occupational stress and performance, suggesting that employees’ mental state is influenced by work-related stress, which in turn decreases professional performance. This relationship can be explained by the Job Demands Theory, developed by Demerouti et al. (2001). From W. B. Schaufeli’s (2017) perspective, in a study where he applied the Job Demands-Resources model, excessive demands and a lack of resources lead to a stress process that results in high levels of burnout, which in turn leads to negative outcomes, including low performance levels. This reasoning leads us to deduce that burnout is the mechanism that explains the relationship between occupational stress and perceived performance, leading to the following hypothesis:

Hypothesis 4.

Burnout has a mediating effect on the relationship between occupational stress and perceived performance.

2.4. Work Regime

The term “work regime” describes the conditions and rules that govern the working relationship between an employer and an employee.

According to Martins (2020), the work regime is defined as the set of rules, conditions, and principles that govern the obligations and rights of employees and the company, such as working hours, weekly workload, and the workplace.

At the legal level, Nogueira (2019) argues that this concept is the normative systematization that regulates the obligations contained in the employment contract and, from an organizational perspective, Chiavenato (2014) thinks that it is an essential part of human resource management and is linked to work planning, such as flexible working hours and types of employment contracts (temporary, part-time, or full-time). In short, the work regime defines how, where, and when employees must perform their duties.

This study will address three work regimes: face-to-face, hybrid, and remote.

2.4.1. Face-to-Face Regime

The face-to-face regime is defined as the model in which employees perform their duties within the physical space of the company, thus promoting direct collaboration, teamwork, and constant supervision.

According to Drucker (1999), this concept is characterized by the performance of activities in a space controlled by the company, allowing for the immediate and fluid exchange of information, which facilitates communication and coordination between work teams. Gil (2010) states that face-to-face work allows interaction and socialization among employees, creating a more collaborative work environment that is conducive to the development and strengthening of the company’s culture. Pires and Macêdo (2016) emphasize that this regime benefits interpersonal relationships by promoting contact, facilitating easier and more immediate problem-solving, and fostering connections in the workplace.

2.4.2. Hybrid Regime

The hybrid work regime is a modality that combines face-to-face and remote work, allowing employees to alternate according to the company’s needs.

Harker and MacDonnell (2012) state that as this model allows for alternation between two work regimes (face-to-face and remote), there is greater autonomy and a more defined alignment between work and personal life demands.

Duffy and Powell (2021) describe the hybrid regime as an evolution of teleworking that enables companies to adopt a more flexible approach, allowing employees to balance their personal and professional lives.

Mello and Silva (2022) explain that this modality can be interpreted as a company strategy to promote organizational effectiveness and efficiency, along with employee satisfaction, if it is well-controlled and accompanied by correct and adequate management.

2.4.3. Remote Regime

This work arrangement highlights the importance of technology in remote work, as well as its role in promoting workplace flexibility and decentralization.

Remote work is a method of working outside the company’s premises, utilizing digital information and communication tools to maintain contact with the company (Davenport & Pearlson, 1998). Bailey and Kurland (2002) argue that this model is a flexible working tool in which employees perform their duties in locations other than the company, using digital means to communicate and interact with the rest of the work team. Messenger and Gschwind (2016) state that remote work combines the use of digital tools with geographical flexibility, enabling a balance between personal and professional life (Bessa & Tomás, 2020).

Mello and Silva (2022) explain that this modality can be interpreted as a company strategy to promote organizational effectiveness and efficiency along with employee satisfaction, if it is well-controlled and accompanied by correct and adequate management.

2.4.4. Work Regime and Burnout

Different authors have studied the effect of work schedules on burnout, considering the organizational context, sector of activity, and worker profile.

Face-to-face work can have a significant impact on burnout, as it often involves high exposure to stressors, including long commutes, workplace conflicts, and work overload, despite avoiding social isolation. Maslach and Leiter (2016) argue that personal interaction with coworkers can lead to emotional exhaustion if the work environment is toxic or poorly managed.

Remote work can reduce exposure to stressors, but it increases levels of isolation and makes it more challenging to separate work from personal life. Kniffin et al. (2021) states that this working arrangement can exacerbate the effects of burnout due to the invisibility that employees feel in their workplace. According to Eurofound and the ILO (2017), remote work is associated with longer working hours and a higher frequency of interruptions outside working hours.

The hybrid work regime is considered the most balanced work model, as it combines greater flexibility with social interaction and interpersonal relationships. However, it can also create some anxiety related to the doubt and uncertainty of a variable routine. Gallup (2022) suggests that employees who adopt a hybrid work arrangement experience lower levels of burnout compared to those who work in person or remotely. The ability to choose when to work remotely is directly related to greater well-being and increased productivity (Microsoft Work Trend Index, 2022). This relationship can also be explained by the Job Demands-Resources Theory (Demerouti et al., 2001). From Demerouti’s (2025) perspective, the fact that employees are working remotely may increase their family demands, but it can also offer them a resource in the form of flexibility. The following hypothesis is therefore formulated:

Hypothesis 5.

The work regime has a significant effect on burnout.

2.4.5. Moderating Effect of Work Regime on the Relationship Between Occupational Stress and Burnout

The moderating effect of the work regime on the relationship between occupational stress and burnout has been analyzed by different authors. Generally, the work regime (face-to-face, hybrid, or remote) can either weaken or intensify the effects of occupational stress on burnout, depending on the specific context.

Bakker and Demerouti (2007) argue that the work regime can serve as a moderator, given its impact on the balance between work demands and available resources. Similarly, they argue that more flexible arrangements, such as remote work, can prevent employees from reaching exhaustion. In contrast, more rigid and demanding arrangements (night work) can intensify and fuel the effects of stress on burnout.

The link between stress and burnout is stronger in work arrangements that limit autonomy; therefore, more flexible work models can have a positive effect by reducing the impact of stress on burnout (Maslach & Leiter, 2016). Similarly, W. B. Schaufeli et al. (2009) explain that the type of work directly influences employee commitment, and that overly demanding jobs can cause exacerbated levels of tiredness, fatigue, and distress. In contrast, more balanced work schedules promote well-being and reduce the impact of stress on burnout.

According to the Work Recovery Theory, Geurts and Sonnentag (2006) and Sonnentag and Fritz (2015) demonstrate that jobs with high workloads and low flexibility result in slower and more time-consuming employee recovery, leading to increased levels of exhaustion. When work schedules allow employees to take breaks and have moments of rest, they serve as a moderator in the relationship between stress and burnout, thus helping to avoid and prevent emotional exhaustion. Employees who are working in a hybrid or remote work environment have greater flexibility to manage these breaks. In conclusion, the work schedule can mitigate or intensify the relationship between occupational stress and burnout, acting as a moderate variable. Work schedules that allow for greater flexibility, such as hybrid schedules, reduce the negative effects of stress, while more demanding schedules intensify the impact of stress on burnout. The moderating effect may also depend on factors such as social support, company culture, and specific job demands. This moderating effect is based on the Job Demands-Resources Theory (Demerouti et al., 2001), as the side effects in various domains such as work, family life, and personal life on job demands and resources must be considered. According to Demerouti and Bakker (2023), it can increase demands related to family problems, but at the same time, it can give employees greater flexibility. These authors suggest that organizations should focus on studying these side effects related to the new type of demands and resources. As three work regimes (face-to-face, hybrid, and remote) were considered in this study, the demands and resources related to the different domains are also different. This is the reason that leads us to understand whether the work regime (face-to-face, hybrid, and remote) changes the relationship between work stress and burnout. The following hypothesis is therefore formulated:

Hypothesis 6.

The work schedule has a moderating effect on the relationship between occupational stress and burnout.

The literature review conducted previously led us to study the effect of occupational stress on performance and the mediating effect of burnout in this relationship. We also studied the effect of work schedules on burnout and their moderate effect on the relationship between occupational stress and burnout. The research model presented in Figure 1 summarizes the hypotheses formulated in this study. This research model is based on Job Demands-Resources Theory (Demerouti et al., 2001) and Conservation of Resources Theory. Resources in the workplace are the crucial point of these two theories, as it is considered that employees are motivated to acquire resources to cope with the demands of work (Bakker et al., 2023). However, Job Demands-Resources Theory considers that if job demands can lead to psychological and physiological costs, resources are functional, reducing demands and promoting personal growth (Bakker et al., 2023). On the other hand, when demands are high and resources are low, employees experience high levels of occupational stress, which increases their levels of burnout and decreases their performance levels (Harris et al., 2009; Hobfoll, 2001). On the other hand, the relationship between occupational stress and burnout can be moderated by the work regime, as remote workers may face more demands related to family problems, but they have a resource that is flexibility (Demerouti, 2025). According to Demerouti and Bakker (2023), it is essential to consider the side effects of demands and resources in various areas, including work, family, and personal life.

3. Materials and Methods

3.1. Data Collection Procedure

This study is exploratory and correlational, as we aim to investigate the relationship between occupational work, burnout, and perceived performance, while also examining whether the work regime mediates this relationship. The data collection procedure was non-probabilistic, intentional, and snowball-type (Vilelas, 2025). This study is also cross-sectional, since the data were collected at a single point in time (Vilelas, 2025).

The questionnaire was submitted on the Google Forms online platform and disseminated via LinkedIn, Facebook, and Instagram, as well as sent by email to some organizations, ensuring data confidentiality.

At the beginning of the questionnaire, a summary was provided detailing the informed consent and ensuring the anonymity of participants’ responses. This was followed by a question about their agreement to participate in the study. If the answer was “no,” participants were directed to the end of the questionnaire, and if the answer was “yes,” they proceeded to the next section.

In addition, the questionnaire consists of sociodemographic questions and questions related to the three scales to be used: occupational Stress, Burnout, and Perceived Performance. The data were collected between January and March 2025.

As a selection criterion, it was considered that to participate in this study, individuals had to meet two conditions: work in organizations based in Portugal (in any sector of activity) and be over 18 years of age. Three hundred and thirty individuals began answering the questionnaire, but five did not agree to participate in the study, which is why only the responses given by 325 individuals were considered valid. The individuals included in the sample are over 18 years of age and work in organizations based in Portugal, across various sectors of activity.

3.2. Participants

The sample for this study consists of 325 participants aged between 19 and 71, of whom 74.5% are female and 25.5% are male. In terms of educational attainment, 44% of participants had completed 12th grade or less, 36.6% had a bachelor’s degree, and 19.4% had a master’s degree or higher. In terms of length of service in the company, 8.3% have less than one year of activity, 26.2% have between 1 and 3 years, 16.6% have between 4 and 6 years, 12.3% have between 7 and 10 years, 8.3% have between 11 and 15 years, and 28.3% have more than 15 years. Regarding employment contracts, 15.7% have an indefinite contract, 11.1% have a fixed-term contract, 66.5% have a permanent contract (effective), and 6.8% report having another type of contract. In terms of working arrangements, 7.1% of participants work remotely, 14.8% in a hybrid arrangement, and 78.2% in a face-to-face arrangement. Participants who work in a hybrid regime were asked how many days per week they work remotely, to which 8.3% responded “One day,” 25% “Two days,” 31.3% “Three days,” 12.5% “Four days,” and 22.9% “Variable”.

3.3. Data Analysis Procedure

The data were imported into SPSS Statistics software 30 (IBM Corp., Armonk, NY, USA). In the first phase, the metric qualities of the instruments used in the study were tested. Thus, to test the validity of the instruments measuring occupational stress, performance, and burnout, factor analyses were performed using AMOS Graphics 29 software (IBM Corp., Armonk, NY, USA). Six adjustment indices were considered, for which the following values should be obtained: for chi-square (χ²/df) ≤ 5; for the Tucker Lew-is index (TLI) > 0.90; for the goodness fit index (GFI) > 0.90; for the comparative fit index (CFI) > 0.90; for the root mean square error of approximation (RMSEA) ≤ 0.08 (McCallum et al., 1996); and for the root mean square residual (RMSR), a lower value corresponds to a better fit (Hu & Bentler, 1999). Next, we tested the reliability of the construct for each dimension of each instrument, whose value must be greater than 0–70. Convergent validity was tested by calculating the average extracted variance (AVE), which must be greater than 0.50 (Fornell & Larcker, 1981).

Next, the internal consistency of all dimensions that make up the instruments used was tested by calculating Cronbach’s alpha, which must contain a minimum acceptable value of 0.70 (Bryman & Cramer, 2003).

As for the sensitivity of the items, the median, minimum, maximum, asymmetry, and kurtosis were calculated. The items must have responses at all points, must not have the median close to one of the extremes, and their absolute values of skewness and kurtosis must be below 2 and 7, respectively (Finney & DiStefano, 2013).

To perform the descriptive statistics on the variables under study, t-tests were performed on the sample. The effect of sociodemographic variables on the variables under study was tested using t-student tests for independent samples and the parametric One-Way ANOVA test. Pearson correlations were used to test whether the variables are significantly associated. Hypotheses 1, 2, 3, and 4 were tested using multiple linear regressions. To test hypothesis 5, two One-Way ANOVA tests were performed, as the independent variable was categorical. Hypothesis 6 (moderating effect) was tested in Macro Process 4.2 (Model 1) developed by Hayes (2022).

3.4. Instruments

To measure work-related stress, the occupational Stress Scale developed by Gomes (2010) was employed. This instrument consists of 24 items where the response scale ranges from 0 to 4, with “0” being “No Stress,” 1 “Little Stress,” 2 “Moderate Stress,” 3 “Much Stress,” and 4 “High Stress.” The 24 items are distributed across seven dimensions: relationship with users (items 2, 8, 13, and 21); relationship with managers (items 12, 20, and 24); relationship with colleagues (items 4, 17, and 22); overwork (items 5, 10, 11, and 16); career and pay (items 1, 6, 15, and 19); family problems (items 3, 14, and 23); and working conditions (items 7, 9, and 18). The validity of this instrument was assessed through a seven-dimensional confirmatory factor analysis. The fit indices obtained were adequate or very close to adequate values (χ²/df = 2.51; GFI = 0.88; CFI = 0.95; TLI = 0.93; RMSEA = 0.068; RMSR = 0.055). All items have factor weights greater than 0.50. Once the construct reliability values were calculated, they ranged from 0.81 (stress with users and stress with career and remuneration) to 0.92 (stress with colleagues and stress with family problems). Regarding convergent validity, the AVE values obtained range from 0.52 (stress related to users) to 0.80 (stress related to family problems). As for internal consistency, the Cronbach’s alpha values obtained range from 0.74 (stress with users) to 0.95 (stress with colleagues).

To measure perceived performance levels, the instrument developed by Williams and Anderson (1991) was used. The scale consists of seven items, assessed using a five-point Likert scale where 1 = “Strongly disagree”, 2 = “Disagree”, 3 = “Neither agree nor disagree”, 4 = “Agree”, and 5 = “Strongly agree”. The validity of this instrument was assessed through a confirmatory factor analysis with a single factor. Items 6 and 7 were removed because they had a low factor weight. The adjustment indices obtained were adequate or very close to adequate values (χ²/df = 3.17; GFI = 0.98; CFI = 0.98; TLI = 0.97; RMSEA = 0.082; RMSR = 0.007). For construct reliability, a value of 0.90 was obtained, and for convergent validity, an AVE value of 0.64 was obtained. Regarding internal consistency, Cronbach’s alpha was 0.90.

To measure burnout, the Oldenburg Burnout Inventory instrument was employed, developed by Demerouti and Nachreiner (1998) and adapted to Portuguese by Sinval et al. (2019). This scale consists of 16 items, classified using a Likert scale where 1 = “Strongly disagree”, 2 = “Disagree”, 3 = “Neither agree nor disagree”, 4 = “Agree”, and 5 = “Strongly agree”. These 16 items are distributed across two dimensions: disengagement (items 1, 3, 6, 7, 9, 11, 13, and 15) and exhaustion (items 2, 4, 5, 8, 10, 12, 14, and 16). Items 1, 5, 7, 10, 13, 14, 15, and 16 should be reversed. To test the validity of this instrument, a two-factor confirmatory factor analysis was performed. Items 1, 3, and 7 were removed because they had low factor weights. The fit indices obtained were adequate or very close to adequate values (χ²/df = 3.16; GFI = 0.93; CFI = 0.95; TLI = 0.92; RMSEA = 0.082; RMSR = 0.049). After calculating the construct reliability values, a value of 0.89 was obtained for exhaustion and a value of 0.84 for disengagement. For convergent validity, the AVE values obtained were 0.52 for exhaustion and 0.50 for disengagement. Regarding internal consistency, Cronbach’s alpha values obtained were 0.89 for exhaustion and 0.81 for disengagement.

Regarding item sensitivity, all items in all instruments have responses at all points, and no item has a median close to either extreme. The asymmetry and kurtosis values are below 2 and 7, respectively, which indicates that they do not grossly violate normality (Finney & DiStefano, 2013).

To measure the work regime, the following question was included in the sociodemographic questionnaire: What is your work regime? The answer options were: face-to-face, hybrid, and remote.

4. Results

Since data for all scales were collected at a single point in time, this study may be susceptible to potential common method variance. To examine common method variance, Harman’s one-factor test was used. An exploratory factor analysis was conducted on a single factor. This unrotated factor accounts for only 29.54% of the total variance explained, indicating that common method variance does not pose a potential risk to the present study (Podsakoff et al., 2003). Next, to further test the variance of the common method, two models were examined: one with a single factor and one with ten factors. The fit indices for the one-factor model were not adequate (χ²/df = 6.52; GFI = 0.44; CFI = 0.47; TLI = 0.45; RMSEA = 0.131; RMSR = 0.130). The fit indices for the ten-factor model proved adequate or very close to adequate values (χ²/df = 1.74; GFI = 0.85; CFI = 0.94; TLI = 0.94; RMSEA = 0.048; RMSR = 0.051). The two methods used enable us to conclude that the theoretical conceptualization, which identified ten variables, adequately represents the observed data. The correlations are consistent with the theorized pattern of relationships.

4.1. Descriptive Statistics of the Variables Under Study

To understand the position of the responses given by the participants in this study, descriptive statistics of the variables under study were performed using t-tests for the sample.

The results indicate that the responses given by the participants in this study in all dimensions of occupational stress are significantly above the midpoint of the scale (2), indicating that they experience high levels of stress (

Table 1. Descriptive Statistics of the Variables Under Study.

Variables	t	gl	p	d	Mean	SD
Stress with Users	3.64 ***	324	<0.001	0.20	2.18	0.87
Stress with Managers	5.46 ***	324	<0.001	0.30	2.32	1.08
Stress with Colleagues	3.19 ***	324	<0.001	0.18	2.20	1.11
Stress with Workload	6.31 ***	324	<0.001	0.35	2.33	0.94
Stress with Career and Remuneration	6.23 ***	324	<0.001	0.35	2.30	0.88
Stress with Family Problems	4.93 ***	324	<0.001	0.27	2.26	0.95
Stress with Working Conditions	3.73 ***	324	<0.001	0.21	2.21	1.03
Disengagement	−5.58 ***	324	<0.001	0.31	2.73	0.87
Exhaustion	0.91	324	0.181	0.05	3.04	0.76
Perceived Performance	41.88 ***	324	<0.001	2.32	4.24	0.53

Note. *** p < 0.001.

).

The responses given regarding disengagement are significantly below the midpoint of the scale (3), indicating that the participants in this study exhibit low levels of disengagement. Exhaustion does not differ significantly from the midpoint of the scale (3) (Table 1).

Performance is significantly above the midpoint of the scale (3), indicating that the participants in this study have a high perception of their performance (Table 1).

4.2. Association Between the Variables Under Study

The association between the variables under study was tested using Pearson correlations.

Among the seven dimensions of occupational stress, only stress with users is negatively and significantly associated with performance (

Table 2. Association between the variables under study.

	1.1	1.2	1.3	1.4	1.5	1.6	1.7	2.1	2.2
1.1. Stress with Users	--
1.2. Stress with Managers	0.68 ***	--
1.3. Stress with Colleagues	0.60 ***	0.75 ***	--
1.4. Stress with Workload	0.63 ***	0.59 ***	0.46 ***	--
1.5. Stress with Career and Remuneration	0.56 ***	0.60 ***	0.44 ***	0.54 ***	--
1.6. Stress with Family Problems	0.77 ***	0.65 ***	0.56 ***	0.76 ***	0.56 ***	--
1.7. Stress with Working Conditions	0.53 ***	0.69 ***	0.54 ***	0.52 ***	0.54 ***	0.55 ***	--
2.1. Disengagement	0.35 ***	0.35 ***	0.23 ***	0.42 ***	0.34 ***	0.35 ***	0.026 ***	--
2.2. Exhaustion	0.42 ***	0.36 ***	0.24 ***	0.54 ***	0.30 ***	0.45 ***	0.22 ***	0.70 ***	--
3. Perceived Performance	−0.13 *	−0.07	−0.04	0.01	0.07	−0.05	0.00	−0.25 ***	−0.19 ***

Note. * p < 0.05; *** p < 0.001.

). Disengagement and exhaustion (dimensions of burnout) are positively and significantly associated with all dimensions of occupational stress, with the strongest association being with workload stress (Table 2). In turn, disengagement and exhaustion are negatively and significantly correlated with perceived performance (Table 2).

4.3. Hypotheses

Among the seven dimensions of occupational stress, only stress related to users (β = −0.29; p = 0.002) and stress related to career and remuneration (β = 0.20; p = 0.007) have a significant effect on performance (

Table 3. Effect of occupational stress on perceived performance.

Independent Variable	Dependent Variable	F	p	R2a	β	p
Stress with Users	Perceived Performance	2.81 **	0.008	0.04	−0.29 **	0.002
Stress with Managers					−0.15	0.161
Stress with Colleagues					0.08	0.343
Stress with Workload					0.10	0.272
Stress with Career and Remuneration					0.20 **	0.007
Stress with Family Problems					0.02	0.864
Stress with Working Conditions					0.04	0.575

Note. ** p < 0.01.

). Participants with higher levels of stress tend to have a lower perception of their performance. Participants with higher levels of stress related to their career and remuneration tend to have higher levels of perceived performance. The model explains 4% of the variability in performance perception (Table 3). The model is statistically significant (F (7, 317) = 2.81; p = 0.008) (Table 3). Hypothesis 1 is partially confirmed.

The results indicate that workload has a positive and significant effect on both disengagement (β = 0.30; p < 0.001) and exhaustion (β = 0.46; p < 0.001) (

Table 4. Effect of occupational stress on burnout.

Independent Variable	Dependent Variable	F	p	R2a	β	p
Stress with Users	Disengagement	12.05 ***	<0.001	0.19	0.20 *	0.049
Stress with Managers					0.10	0.230
Stress with Colleagues					−0.10	0.187
Stress with Workload					0.30 ***	<0.001
Stress with Career and Remuneration					0.12	0.070
Stress with Family Problems					−0.06	0.507
Stress with Working Conditions					−0.06	0.406
Stress with Users	Exhaustion	21.30 ***	<0.001	0.30	0.14	0.087
Stress with Managers					0.17	0.061
Stress with Colleagues					−0.12	0.104
Stress with Workload					0.46 ***	<0.001
Stress with Career and Remuneration					−0.01	0.932
Stress with Family Problems					0.04	0.620
Stress with Working Conditions					0.17 *	0.013

Note. * p < 0.05; *** p < 0.001.

). Participants with higher levels of stress with workload revealed higher levels of disengagement and exhaustion. The results also showed that stress experienced by users has a positive and significant effect on disengagement (β = 0.20; p = 0.049) and stress related to conditions has a positive and significant impact on exhaustion (β = 0.17; p = 0.013) (Table 4). Participants with higher levels of stress with users have higher levels of disengagement. Participants with higher levels of stress due to working conditions tend to experience higher levels of exhaustion. The models explain 19% of the variability in disengagement and 30% of the variability in exhaustion. Both models are statistically significant (F (7, 317) = 12.05; p < 0.001) and (F (7, 317) = 21.30; p < 0.001) (Table 4). Hypothesis 2 is partially confirmed.

The results indicate that only disengagement has a negative and significant effect on perceived performance (β = −0.23; p = 0.002) (

Table 5. Effect of burnout on perceived performance.

Independent Variable	Dependent Variable	F	p	R2a	β	p
Disengagement	Perceived Performance	10.78 ***	<0.001	0.06	−0.23 **	0.002
Exhaustion					0.04	0.645

Note. ** p < 0.01; *** p < 0.001.

). Participants with higher levels of disengagement tend to have a lower perception of their performance. The model explains 6% of the variability in performance perception (Table 5). The model is statistically significant (F (2, 322) = 10.78; p < 0.001) (Table 5). The results partially support Hypothesis 3.

This hypothesis presupposes a mediating effect; therefore, the procedures outlined by Baron and Kenny (1986) were followed. Only mediating effects that met the conditions assumed by these authors will be tested. A multiple linear regression was performed in two steps. In the first step, the predictor variable was introduced as an independent variable, and in the second step, the mediating variable was introduced.

The results indicate that disengagement has a mediating effect on the relationship between stress with users and performance perception (β = −0.23; p < 0.001) (

Table 6. The mediating effect of burnout on the relationship between occupational stress and perceived performance.

Variable	Perceived Performance
	β Step 1	β Step 2
Stress with Users	−0.13 *	−0.05
Disengagement		−0.23 ***
F	5.72 *	11.09 ***
R2a	0.02	0.06
Δ		0.04 ***

Note. * p < 0.05; *** p < 0.001.

). When the mediating variable was introduced into the regression equation, the effect of stress with users on performance perception ceased to be significant. The model explains 6% of the variability in performance perception (Table 6). The model is statistically significant (F (2, 322) = 11.09; p < 0.001) (Table 6). The Sobel test (Z = 2.32; p = 0.010) confirmed the total mediation effect. The results partially support hypothesis 4.

This hypothesis was tested using the parametric One-Way ANOVA test after testing the respective assumptions.

The results indicate that the work regime has a statistically significant effect on disengagement (F (2, 322) = 3.44; p = 0.033) (

Table 7. Effect of work regime on burnout.

Variable	ANOVA One Way		Work Regime. A	Work Regime. B	TuKey HSD
	F	p			Mean Difference (A–B)	p
Disengagement	3.44 *	0.033	Face-to-face	Remote	−0.48 *	0.029
Exhaustion	0.95	0.390	-	-	-	-

Note. * p < 0.05.

). Participants in the face-to-face work regime (M = 2.68, SD = 0.87) exhibit lower levels of disengagement compared to those in remote work (M = 3.16, SD = 0.91) (Table 7). The results partially support hypothesis 5.

The results indicate that the work regime does not moderate the relationship between occupational stress and disengagement, as the confidence interval for all dimensions contains zero (

Table 8. The moderating effect of the work regime on the relationship between occupational stress and disengagement.

Variable	B	SE	t	p	95% IC
	Stress with Users → Disengagement (R2 = 0.14; p < 0.001)
Constant	2.18 ***	0.27	7.82 ***	<0.001	[1.63; 2.72]
Stress with Users	0.16	0.12	1.34	0.182	[−0.07; 0.38]
Work Regime	−0.14	0.19	−0.72	0.475	[−0.52; 0.24]
SU × WR	0.14	0.08	1.77	0.078	[−0.02; 0.30]
Variable	B	SE	t	p	95% IC
	Stress with Managers → Disengagement (R2 = 0.15; p < 0.001)
Constant	2.13 ***	0.25	8.38 ***	<0.001	[1.63; 2.63]
Stress with Managers	0.14	0.10	1.44	0.148	[−0.05; 0.34]
Work Regime	−0.05	0.17	−0.27	0.787	[−0.40; 0.30]
SM × WR	0.10	0.07	1.58	0.116	[−0.02; 0.24]
Variable	B	SE	t	p	95% IC
	Stress with Colleagues → Disengagement (R2 = 0.08; p < 0.001)
Constant	2.20 ***	0.24	9.17 ***	<0.001	[1.72; 2.67]
Stress with Colleagues	0.11	0.10	1.13	0.261	[−0.08; 0.30]
Work Regime	0.10	0.16	0.64	0.521	[−0.21; 0.42]
SC × WR	0.06	0.07	0.81	0.417	[−0.08; 0.19]
Variable	B	SE	t	p	95% IC
	Stress with Workload → Disengagement (R2 = 0.19; p < 0.001)
Constant	1.79 ***	0.27	6.57 ***	<0.001	[1.25; 2.32]
Stress with Workload	0.33 **	0.11	3.11 **	0.002	[0.12; 0.54]
Work Regime	−0.05	0.19	0.26	0.793	[−0.32; 0.42]
SW × WR	−0.04	0.07	1.58	0.588	[−0.10; 0.17]
Variable	B	SE	t	p	95% IC
	Stress with Career and Remuneration → Disengagement (R2 = 0.13; p < 0.001)
Constant	1.82 ***	0.31	5.95 ***	<0.001	[1.21; 2.42]
Stress with Career and Remuneration	0.29 *	0.12	2.36 *	0.019	[0.05; 0.53]
Work Regime	0.10	0.22	0.48	0.632	[−0.33; 0.53]
SCR × WR	0.04	0.09	0.41	0.685	[−0.13; 0.21]
Variable	B	SE	t	p	95% IC
	Stress with Family Problems → Disengagement (R2 = 0.14; p < 0.001)
Constant	2.16 ***	0.29	7.50 ***	<0.001	[1.59; 2.73]
Stress with Family Problem	0.17	0.11	1.52	0.129	[−0.05; 0.39]
Work Regime	−0.10	0.21	−0.49	0.622	[−0.51; 0.31]
SFP × WR	0.11	0.08	1.33	0.184	[−0.005; 0.26]
Variable	B	SE	t	p	95% IC
	Stress with Working Conditions → Disengagement (R2 = 0.09; p < 0.001)
Constant	2.33 ***	0.26	8.81 ***	<0.001	[1.81; 2.85]
Stress with Working Conditions	0.06	0.11	0.57	0.571	[−0.15; 0.27]
Work Regime	−0.06	0.18	−0.34	0.731	[−0.42; 0.30]
SWC × WR	0.12	0.07	1.64	0.101	[−0.02; 0.26]

Note. * p < 0.05; ** p < 0.01; *** p < 0.001.

).

The results indicate that the work regime has only a moderate effect on the relationship between stress and working conditions, and exhaustion (

Table 9. The moderating effect of the work regime on the relationship between occupational stress and exhaustion.

Variable	B	SE	t	p	95% IC
	Stress with Users → Exhaustion (R2 = 0.17; p < 0.001)
Constant	2.21 ***	0.24	9.26 ***	<0.001	[1.74; 2.68]
Stress with Users	0.36 ***	0.10	3.59 ***	<0.001	[0.16; 0.55]
Work Regime	0.05	0.17	0.83	0.829	[−0.29; 0.36]
SU × WR	0.01	0.07	0.98	0.980	[−0.13; 0.13]
Variable	B	SE	t	p	95% IC
	Stress with Managers → Exhaustion (R2 = 0.14; p < 0.001)
Constant	2.55 ***	0.22	11.41 ***	<0.001	[2.11; 3.00]
Stress with Managers	0.17	0.09	1.93	0.053	[−0.01; 0.34]
Work Regime	−0.08	0.17	−0.52	0.598	[−0.39; 0.22]
SM × WR	0.06	0.06	1.07	0.284	[−0.05; 0.18]
Variable	B	SE	t	p	95% IC
	Stress with Colleagues → Exhaustion (R2 = 0.06; p < 0.001)
Constant	2.65 ***	0.21	12.59 ***	<0.001	[2.24; 3.06]
Stress with Colleagues	0.13	0.09	1.45	0.149	[−0.05; 0.30]
Work Regime	0.02	0.14	0.13	0.897	[−0.26; 0.30]
SC × WR	0.03	0.06	0.51	0.611	[−0.09; 0.15]
Variable	B	SE	t	p	95% IC
	Stress with Workload → Exhaustion (R2 = 0.29; p < 0.001)
Constant	2.05 ***	0.22	9.27 ***	<0.001	[1.62; 2.49]
Stress with Workload	0.43 ***	0.09	4.94 ***	<0.001	[0.26; 0.59]
Work Regime	−0.02	0.15	−0.15	0.882	[−0.32; 0.28]
SW × WR	−0.01	0.06	0.15	0.882	[−0.10; 0.12]
Variable	B	SE	t	p	95% IC
	Stress with Career and Remuneration → Exhaustion (R2 = 0.10; p < 0.001)
Constant	2.55 ***	0.27	9.36 ***	<0.001	[2.01; 3.08]
Stress with Career and Remuneration	0.18	0.11	1.65	0.101	[−0.04; 0.40]
Work Regime	−0.09	0.20	−0.46	0.642	[−0.48; 0.30]
SCR × WR	0.06	0.08	0.80	0.423	[−0.09; 0.22]
Variable	B	SE	t	p	95% IC
	Stress with Family Problem → Exhaustion (R2 = 0.21; p < 0.001)
Constant	2.48 ***	0.24	10.29 ***	<0.001	[2.00; 2.95]
Stress with Family Problem	0.25 **	0.09	2.63 **	0.009	[0.06; 0.44]
Work Regime	−0.20	0.17	−1.14	0.255	[−0.54; 0.14]
SFP × WR	0.09	0.07	1.30	0.195	[−0.04; 0.22]
Variable	B	SE	t	p	95% IC
	Stress with Working Conditions → Exhaustion (R2 = 0.06; p < 0.001)
Constant	2.97 ***	0.24	12.64 ***	<0.001	[2.51; 3.43]
Stress with Working Conditions	−0.01	0.09	−0.07	0.941	[−0.19; 0.18]
Work Regime	−0.22	0.16	−1.35	0.178	[−0.54; 0.10]
SWC × WR	0.13 *	0.07	1.98	0.048	[0.01; 0.26]

Note. * p < 0.05; ** p < 0.01; *** p < 0.001.

). For participants in remote and hybrid work regimes, compared to those in face-to-face work, working conditions become a relevant source of stress, contributing to increased levels of exhaustion (Figure 2).

5. Discussion

The primary objective of this study was to examine the relationship between occupational stress and perceived performance, and whether this association was mediated by burnout. In addition, we sought to understand whether the work regime (face-to-face, hybrid, and remote) moderates the relationship between occupational stress. All these relationships are based on Job Demands-Resources Theory (Demerouti et al., 2001) and Resource Conservation Theory (Hobfoll, 1989).

Firstly, Hypothesis 1 was partially confirmed. Only stress related to users and stress related to career and remuneration have a significant association with performance. When participants feel high levels of stress with users, their perception of performance is lower. These results align with the existing literature. According to Chen et al. (2022), a significant association exists between occupational stress and perceived performance This result can be interpreted in light of the Job Demands-Resources Theory (Demerouti et al., 2001), which posits that when demands are high (i.e., demanding customers) and employees’ resources for dealing with these demands are scarce, employee performance is negatively affected (W. B. Schaufeli, 2017).

On the other hand, when their stress with career and remuneration is higher, their perception of performance increases. These results contradict the findings in literature. Employees may feel high levels of stress regarding their career and remuneration because they perceive their performance as high and believe they should be rewarded with career progression and higher remuneration. Another factor may be that employees consider their career and remuneration as a resource they want to maintain, which can cushion the wear and tear caused by work demands, highlighting the importance of good performance (Demerouti & Bakker, 2023).

Secondly, Hypothesis 2 was partially confirmed, as only stress with users and stress with workload have a significant effect on disengagement. Participants with high levels of stress, whether due to users or workload, exhibit higher levels of disengagement. In turn, only stress with workload has a positive and significant effect on exhaustion. Participants with high stress due to workload have high levels of exhaustion. These results are consistent with literature. According to Freitas et al. (2023), workload is the dimension of occupational stress that has the most potent effect on both disengagement and exhaustion. According to Job Demands-Resources Theory (Demerouti et al., 2001), when demands are high, employees feel more exhausted, and when resources are low, employees respond with higher levels of disengagement. These results are consistent with what this theory establishes. When workload demands are high, employees feel higher levels of exhaustion. On the other hand, when resources to deal with user demands and work overload are scarce, they react with higher levels of disengagement (Demerouti et al., 2001).

Thirdly, Hypothesis 3 was partially confirmed. Only disengagement has a negative and significant effect on performance. Participants with high levels of disengagement exhibited lower performance levels. These results are consistent with literature. Burnout has a significant negative association with perceived performance (Freire Palacios et al., 2024; Lei et al., 2025). According to Demerouti (2025), disengagement is a defensive mechanism, which means that as employees become less involved in their work, their job performance declines. As the task performance dimension of the instrument developed by Williams and Anderson (1991) was used to measure performance, the results obtained in this study are in line with what Demerouti (2025) suggests.

Fourth, Hypothesis 4 was partially confirmed. Disengagement has a total mediating effect on the relationship between stress with users and perceived performance. Stress with users increases disengagement and decreases perceived performance. These results are consistent with literature. According to Chen et al. (2022), the mental state of employees is influenced by work-related stress, which in turn affects their professional performance. These results can also be interpreted in light of the Job Demands-Resources Theory (Demerouti et al., 2001), as when resources for dealing with user demands are scarce, employees experience high levels of disengagement, and their task performance declines as they become less involved with their work.

Fifth, Hypothesis 5 was partially confirmed. The work regime only has a significant effect on disengagement. Participants who work in person differ significantly from those who work remotely, with the latter showing significantly higher levels of disengagement. These results align with those reported by some authors. From the perspective of Kniffin et al. (2021), remote working arrangements can exacerbate the effects of burnout due to the invisibility that employees feel in their workplace. In terms of efficiency and flexibility, there are also challenges related to social interactions and nonverbal cues (Hanzis & Hallo, 2024). The results are also in line with what Demerouti (2025) tells us, that remote work can increase demands on family and personal life problems, but that flexibility can be a resource. However, if the demands of family problems are high and the employee lacks flexibility, the lack of this resource can increase levels of disengagement. This explains why disengagement is significantly higher among remote workers.

Finally, Hypothesis 6 was partially confirmed. The work regime moderates the relationship between stress, working conditions, and exhaustion. For participants in hybrid and remote work regimes, compared to those in face-to-face work regimes, working conditions become more relevant by increasing their levels of exhaustion. These results contradict existing literature. From the perspective of Bakker and Demerouti (2007), more flexible regimes, such as remote work, can prevent employees from reaching exhaustion, while more rigid and demanding regimes (night work) can intensify and foster the effects of stress on burnout. These results reflect the disparity in participants working in each of the work regimes, as the majority are in face-to-face work. However, some authors claim that remote work can lead to higher levels of stress. In this sense, Kniffin et al. (2021) argue that the lack of visibility of remote work can cause high levels of burnout. In turn, Hanzis and Hallo (2024) highlight the lack of visibility and nonverbal cues in remote work compared to face-to-face work.

It is also worth noting that the participants in this study reported high levels of stress and perceived performance, but low levels of disengagement. Regarding exhaustion, the values presented do not differ significantly from the midpoint of the scale.

5.1. Limitations and Future Research

This study has several limitations that should be considered when interpreting the results.

Firstly, this study employed a cross-sectional research design, which may limit its ability to establish a causal relationship between the analyzed variables.

In other words, although significant associations were found between occupational stress, burnout, and perceived performance, we cannot guarantee that one variable causes the other; we can only say that they are correlated at a given moment (Creswell & Creswell, 2018). Furthermore, it is not a specific organization or sector, since the conditions for participating in the study were age (over 18) and working in organizations based in Portugal (from any sector of activity). As a result, it was impossible to calculate the number of participants so that the sample would be representative of the population.

Another limitation may be related to the data collected through the questionnaire. Since the participants themselves completed the questionnaire, errors may have occurred, such as socially acceptable and dishonest responses, as well as similar or standardized responses due to a lack of attention. In other words, these errors may affect the accuracy and reliability of the responses, causing the data collected to fail to reflect reality (Podsakoff et al., 2003) accurately.

The composition of the sample may also be a limitation of this study, since it only included participants working in companies based in Portugal. Thus, the results may be compromised and limited to different cultural and organizational contexts (Bryman, 2016).

In addition, most participants were in person, which may have affected the statistical effects in the moderating analyses.

Finally, the fact that control variables were not used in the statistical analyses related to hypothesis testing can be considered a limitation.

Given these limitations, it is important to propose some suggestions for future research. First, longitudinal studies may be relevant as they allow the evolution of variables to be observed over time, establishing stronger causal relationships (Taris & Kompier, 2014). Another suggestion is to adopt several different methods, combining quantitative data with qualitative interviews or objective performance indicators, contributing to a more accurate and comprehensive understanding of the results (Creswell & Poth, 2017).

Analyzing the impact of the sector of activity and the type of role performed by participants is another suggestion to consider, given that different work contexts can generate different sources of stress (W. Schaufeli, 2021). It could also be relevant to add and study other moderating variables (social support, organizational leadership, feedback culture, or work–life balance), as these have also been shown to influence the relationship between stress and burnout (Bakker & Demerouti, 2017; Hobfoll et al., 2018).

Finally, considering the importance and relevance of hybrid and remote working arrangements in recent years, further studies are suggested to explore in more detail the effects these arrangements have on long-term well-being and productivity (Kniffin et al., 2021; Microsoft Work Trend Index, 2022).

By applying these suggestions in future research, a more comprehensive understanding of the dynamics between stress, burnout, and performance may be achieved, as well as more effective organizational practices and strategies for promoting employee mental health and optimal performance.

5.2. Theoretical Implications

The results obtained in this study are consistent with the existing literature, allowing for further reflection on the relationship between occupational stress, burnout, and employee performance.

First, it confirms that high job demands (such as stress with users or workload) are associated with higher levels of burnout (Demerouti et al., 2001).

The “Job Demands-Resources” model is supported by the finding that burnout serves as a mediator in the relationship between stress and performance (Bakker & Demerouti, 2017; Che et al., 2022; Demerouti, 2025).

In this study, participants who work remotely exhibit higher levels of disengagement, providing new insights for the literature. Demerouti and Bakker (2023) recommended studying the side effects of demands and resources across various domains of life, including work, family, and personal life. This study confirms this need, as this result can be explained by the fact that employees have high demands with family and personal problems, and their resources (such as flexibility) are low (Demerouti, 2025).

The work regime, acting as a moderating variable, confirms the conclusions of Maslach and Leiter (2016), which suggest that more flexible regimes mitigate the adverse effects of occupational stress. In contrast, the effects of occupational stress are intensified in less flexible regimes. Another result that we can consider innovative is that for participants who are working remotely or in a hybrid regime, stress related to working conditions increases their levels of exhaustion. Once again, this highlights the importance of studying the side effects of demands and resources in different areas of life, as suggested by Demerouti and Bakker (2023).

Another theoretical implication is that stress related to working conditions is one of the most critical dimensions with a direct impact on levels of exhaustion; therefore, it is essential to consider contextual and environmental factors (Hirschle & Gondim, 2020).

Finally, it is worth noting that this study makes a positive contribution to the work environment by enabling the analysis of the current effects of the COVID-19 pandemic on work practices and employee well-being across various work arrangements.

5.3. Practical Implications

The results obtained allow us to identify practical implications relevant to the business context.

We recommend adopting effective methods to monitor and control sources of stress, as stress with users and working conditions has been shown to impact performance levels.

According to the results, employees in hybrid regimes exhibit lower levels of disengagement and burnout, which aligns with Gallup’s (2022) findings. It is therefore essential for companies to consider adopting this work regime to enhance employee well-being and productivity.

Maslach and Leiter (2016) and the WHO (2019) recommend that organizations’ human resources management implement measures such as regular breaks, feedback sessions, and wellness activities to reduce burnout levels. All of these measures can serve as work resources that mitigate the effects of job demands on professional burnout, thereby preventing employees from experiencing high levels of burnout (Demerouti & Bakker, 2023). According to Job Demands-Resources Theory (Demerouti et al., 2001), interactions between job demands and resources are fundamental to professional burnout and motivation. Throughout the study, it was found that female participants and younger participants experienced higher levels of stress and burnout. Therefore, it is necessary to develop practices such as mentoring and coaching programs, as well as psychological support.

Stress related to management is associated with burnout, even if it is indirect. Therefore, training focused on leadership, communication, and people management is recommended, as suggested by Cooper and Cartwright (1994). As suggested by Demerouti (2025), it is also recommended that human resource management in organizations integrate the principles of resource conservation theory (Hobfoll, 1989) and Job Demands-Resources Theory (Demerouti et al., 2001) into organizational practices to create environments that promote motivation, engagement, and success among employees in the face of constant professional challenges.

6. Conclusions

Based on the study conducted, it is possible to state that these results confirm that occupational stress, specifically stress related to users, has a negative and significant impact on the perceived performance level of workers. This conclusion aligns with studies conducted by Freire Palacios et al. (2024) and Lei et al. (2025).

On the other hand, it is also possible to confirm that burnout, especially in terms of disengagement, mediates the relationship between stress with users and performance. As previously analyzed by Maslach and Leiter (2016) and W. B. Schaufeli et al. (2009), this mediation highlights the significance of burnout as a contributing factor to stress levels in organizations. According to the Job Demands-Resources Theory (Demerouti et al., 2001), it can be concluded that employees in this study, who lack resources to meet user demands, become less involved in their work, and their task performance declines.

Another relevant conclusion of this study relates to the moderating effect of the work regime. Workers who adopt a remote working method tend to experience higher levels of disengagement and a consequent increased susceptibility to burnout. Employees who are working remotely beyond the demands of their job often have to deal with demands related to family issues. If they have more flexibility, this can serve as a resource and mitigate the effects of these demands; however, if this resource fails, levels of disengagement increase (Demerouti, 2025). As confirmed by Gallup (2022), the hybrid work regime has proven to be a method that promotes higher levels of well-being and performance.

As presented in the Job Demands-Resources Model (Bakker & Demerouti, 2017), this study also confirmed that stress related to workload and working conditions is significantly associated with burnout, particularly disengagement and exhaustion. These results confirm that demands related to workload and working conditions are high, leading to exhaustion, and that resources to cope with these demands are scarce, leading to high levels of disengagement (W. B. Schaufeli, 2017). In conclusion, companies need to adopt strategies that reduce stress levels by fostering healthier work environments and promoting the adoption of more flexible work arrangements. These practices lead to individual well-being and enhance business performance.