Burnout Among Healthcare Workers: From Evaluation to Intervention for Holistic Well-Being

1. Introduction

Prolonged exposure to stressful and unfavorable working conditions tends to erode well-being. Over time, this sustained stress can culminate in burnout, when employees become emotionally and physically drained and disengaged from their work [1,2]. Burnout is a global issue characterized by a work-induced syndrome of chronic stress that has not been successfully managed [3]. In the 11th revision of the International Classification of Diseases of World Health Organization (ICD-11), burnout is defined as an occupational phenomenon with risk of harming health, comprising three factors: physical and emotional exhaustion, cynicism or mental distance (i.e., detachment and negativity toward work), and reduced professional efficacy [4].

In the healthcare sector, burnout has become a critical concern due to high job demands and emotional strain. Even before the COVID-19 pandemic, burnout among healthcare workers was recognized as a serious issue, being the subject of urgent calls to action in healthcare systems [5]. Large-scale studies and reviews indicate that prior to 2020, about one in three clinicians experienced burnout symptoms. During the COVID-19 pandemic, this proportion increased dramatically, with a meta-analysis found that over half of healthcare workers (52%) met burnout criteria, with rates as high as 66% among physicians and nurses [6]. Between the causes, frontline providers such as physicians, nurses, and allied health professionals often report long working hours, heavy workloads, imbalances in duty allocation, physically strenuous work, resource constraints, and exposure to suffering [7]. Considering this evidence, burnout in healthcare is now recognized as a public and occupational health priority, demanding urgent attention and action [8].

At an individual level, workers with burnout often suffer from higher rates of insomnia, depression, anxiety, and psychosomatic complaints. Moreover, previous evidence has found that clinicians experiencing burnout are more prone to substance use [9] and even suicidal ideation [1]. At an organization level, the effects of burnout are equally alarming, as burnout can impair job performance and increase the likelihood of errors, threatening patient safety and quality of care. For instance, studies have linked higher burnout among physicians and nurses to more frequent medical mistakes and lower patient satisfaction [10,11,12]. Finally, at a system level, burnout drives higher absenteeism and turnover as exhausted clinicians are more likely to cut back their work hours or leave the profession, exacerbating workforce shortages [13,14,15,16]. This turnover incurs significant financial costs, as replacing an experienced nurse or physician is expensive and can reduce organizational productivity [17,18].

Thus, if unmitigated, the burnout crisis undermines healthcare delivery by diminishing care quality, increasing costs, and straining the capacity of health systems to meet patient needs. It is therefore unsurprising that burnout has been officially acknowledged as a work-related illness or occupational disorder in several European nations [19]. Moreover, the European Occupational Safety and Health Framework Directive (89/391/EEC-OSH) [20] requires employers to assess all potential risks to workers’ safety and health. To meet the requirements of this directive, organizations need to have access to valid and reliable methodologies capable of assessing employees’ levels of burnout [21].

Theoretical models of occupational stress, such as the Job Demands–Resources model, explain burnout as the outcome of chronically high job demands coupled with insufficient resources (e.g., lack of control or support) [22]. However, current research points to a range of psychosocial risk factors in the work environment as key contributors to burnout in healthcare settings. Among these stressors, we can find work process inefficiencies (e.g., computerized order entry and documentation), excessive workloads (e.g., work hours, overnight call frequency, nurse-patient ratios), work-home conflicts, organizational climate factors (e.g., management culture; lack of physician-nurse collaboration, value congruence, opportunities for advancement, and social support), and deterioration in control, autonomy, and meaning at work [23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38]. Moral distress, stemming from factors such as perceived powerlessness, unnecessary care, inadequate informed consent, and false hope [39], is also a significant predictor of burnout among nurses [31]. Recognizing these risk factors is crucial because they are modifiable. Theory and evidence together indicate that improving the psychosocial work environment can mitigate burnout and enhance well-being [40].

Given the multifaceted nature of burnout, a multidimensional assessment approach is essential to comprehensively capture its scope and underlying determinants. Accordingly, the present study employs a comprehensive set of validated instruments to evaluate work-related psychosocial risk factors and their predictive role in burnout among healthcare professionals.

This study encompasses multiple dimensions of burnout syndrome and different factors of the psychosocial work environment. Multidomain evaluation aligns with a holistic well-being perspective by recognizing that improving healthcare workers’ well-being requires addressing both the work environment and the individual’s health. Such a holistic assessment is not only diagnostic but also forms the foundation for intervention. In other words, by rigorously evaluating the problem, the present study aims to inform evidence-based strategies to improve healthcare workers’ well-being. Understanding exactly which risk factors (e.g., workload, lack of support, or work-home imbalance) are most strongly related to burnout will enable targeted organizational changes and supportive interventions.

Therefore, this study aims to: 1) describe the burnout dimensions of the healthcare workers; 2) describe the levels of psychosocial risks to which healthcare workers are exposed; and 3) examine the predictive role of psychosocial work-related risks in the development of burnout. Based on these findings, we discuss the implications for integrated interventions that address organizational dimensions of healthcare workers’ well-being.

2. Materials and Methods

2.1. Participants

This cross-sectional study employed a non-probabilistic convenience sampling approach, using a snowball recruitment method. Participants were recruited via posts shared on social media platforms (such as Facebook and LinkedIn) and through university students who agreed to distribute the study within their personal networks, from May to September 2025. Eligibility criteria included being a healthcare professional at least 18 years old and being fluent in European Portuguese.

2.2. Instruments

In addition to a socio-demographic questionnaire that included items on age, gender, educational level, and marital status, participants completed the Portuguese versions of the following instruments.

The psychosocial risk factors scale (INSAT-ERPS) is a Portuguese self-report questionnaire designed to assess working-related psychosocial risk factors. It includes 44 items organized into seven categories: work intensity (11 items; e.g., “Frequent interruptions”), working hours (6 items; e.g., “Exceeding normal working hours”), lack of autonomy (4 items; e.g., “Not being able to participate in decisions regarding my work”), work social relations (8 items; e.g., “Needing help from colleagues and not receiving it”), employment relations (6 items; e.g., “I feel exploited most of the time”), emotional demands (5 items; e.g., “Being exposed to others’ difficulties and/or suffering”), and Work Values (4 items; e.g., “My professional conscience is undermined”) [41].

All items are rated on a 6-point Likert scale ranging from 0 (not exposed) to 5 (exposed with high discomfort). INSAT_ERPS has shown good internal consistency, with a reliability coefficient above 0.85 [41]. In a recent study composed by 356 participants, the INSAT Cronbach’s alpha coefficients were 0.972 for the total scale and, respectively, 0.909 for work intensity, 0.897 for working hours, 0.855 for lack of autonomy, 0.814 for work relations, 0.895 for employment relations, 0.941 for emotional demands, and 0.893 for Work Values [42]. Scores starting at 1.60 indicate a medium risk level, while scores above 3.30 indicate high risk [42]. Cronbach’s alpha values for this sample were 0.932 for total scale and for each category: 0.898 for work intensity, 0.879 for working times, 0.835 for lack of autonomy, 0.915 for work social relations, 0.882 for employment relations with the organization, 0.919 for emotional demands, and 0.898 for work values.

Burnout Assessment Tool (BAT) [43]. The BAT is a self-report measure that conceptualizes burnout as a syndrome comprising four core dimensions—exhaustion, mental distance, emotional impairment, and cognitive impairment—assessed through 23 items. All items are rated on a five-point Likert scale ranging from 1 (“Never”) to 5 (“Always”) [44]. The four dimensions of the BAT evaluated: (a) Exhaustion (eight items, e.g., “At work, I feel mentally exhausted”), which reflects a severe depletion of energy resulting in both physical (e.g., tiredness, weakness) and mental (e.g., feeling drained and worn out) fatigue. Typical symptoms include lacking the energy to begin new tasks, feeling completely exhausted after a workday, becoming fatigued after minimal effort, and being unable to relax after work. (b) Emotional impairment (five items, e.g., “At work, I feel unable to control my emotions”), which denotes intense emotional reactions and feelings of being overwhelmed by one’s emotions. Specific indicators include frustration and anger at work, irritability, overreacting, feeling upset or sad without a clear reason, and difficulties controlling emotions in the workplace. (c) Cognitive impairment (five items, e.g., “At work, I have trouble staying focused”), which captures difficulties in memory, attention, and concentration, as well as reduced cognitive performance. Typical symptoms include problems thinking clearly or learning new information, forgetfulness, indecisiveness, and poor concentration at work. (d) Mental distance (five items, e.g., “I struggle to find any enthusiasm for my work”), which reflects psychological detachment from work, often expressed as a strong reluctance or aversion to engaging in work-related activities. Common manifestations include mental or physical withdrawal, avoidance of interactions with colleagues, clients, or customers, indifference, cynicism, and a lack of enthusiasm or engagement as tasks may be performed almost automatically [43]. Cronbach’s alpha values for this sample were 0.943 for all scale and for each category: 0.933 for exhaustion, 0.899 for mental distance, 0.844 for cognitive impairment, and 0.880 for emotional impairment.

2.3. Procedures

2.3.1. Data Collection

This research followed a descriptive, observational, and cross-sectional quantitative design. Authorization to use the original instruments was formally obtained from their respective authors, and the study received approval from the local ethics committee (reference: FCHS/PI475/23). All participants provided informed consent prior to participation, after being assured of the confidentiality and anonymity of their data.

2.3.2. Data Analysis

All statistical analyses were performed using IBM SPSS statistical program for Windows, version 30.0 (SPSS Inc., Chicago, IL, USA). A significance level of α = 0.05 was adopted. Descriptive statistics were computed for continuous variables, including the mean (M), standard deviation (SD), and range (minimum and maximum values), while categorical variables were summarized using absolute frequencies (n) and relative percentages (%). Pearson’s bivariate correlations were performed to examine the relationships among the INSAT_ERPS subscales (work-related psychosocial risks), and the BAT subscales (burnout dimensions). Correlations were interpreted according to Cohen’s guidelines, where r values of 0.10, 0.30, and 0.50 represent small, medium, and large effects, respectively [45].

To examine the predictive role of the INSAT_ERPS subscales on burnout dimensions, multiple linear regression analyses were conducted. Each core dimension of the BAT (exhaustion, mental distance, emotional impairment, and cognitive impairment) was entered as a dependent variable in separate regression models. The seven subscales (work intensity, working hours, lack of autonomy, work social relations, employment relations, emotional demands, and Work Values) were simultaneously entered as independent predictors. Each model tested the extent to which the different facets of work-related psychosocial risks predicted specific burnout symptoms.

Model significance was evaluated using the F-test, and the amount of explained variance was expressed by the coefficient of determination (R²). The standardized regression coefficients (β) and their respective p-values were examined to identify significant predictors. Assumptions of linearity, homoscedasticity, and normality of residuals were verified. Multicollinearity was assessed through the Variance Inflation Factor (VIF), with values below 5 indicating acceptable levels of independence among predictors [46]. Only predictors with p < 0.05 were considered statistically significant.

3. Results

3.1. Sample

The sample was composed of 154 participants (M_age = 41,6; SD_age = 11,2; Age range = 21–67; 92.2% female). All participants were employed in the health care sector. Concerning their professional role, 43.5% were nurses, 22.1% were physicians, and 34.4% were other health professionals, including physiotherapists, psychologists, social workers, and allied health technicians. Regarding educational level, most participants held a university degree (59.1%) or a master’s degree (33.1%). A small number had completed secondary education (3.9%) or a doctoral degree (3.2%). In terms of marital status, 63.9% were married or in a civil partnership, 29.0% were single, and 6.5% were divorced or separated. Most participants worked in public institutions (61.3%), while 25.8% were employed in the private sector and 11.6% in public–private partnerships. Concerning employment type, 81.9% held a permanent contract, 7.7% were on a fixed-term contract, 9.0% worked under temporary or freelance arrangements, and 0.6% were self-employed.

3.2. Burnout Assessment Among Healthcare Professionals

The descriptive analysis of the BAT (mean scores) is presented in Table 1. Descriptive analysis of BAT scores (N=154). The scale establishes two cut-off points: (a) scores beginning at 2.59 indicate burnout risk, and (b) scores exceeding 3.02 suggest positive burnout diagnoses [44]. As shown, and using these cut-off points, only the Exhaustion core symptom category indicates Burnout risk (M>2.59) for all healthcare professionals.

Across all healthcare professionals, exhaustion is the predominant burden, with nurses appearing most affected overall (especially on exhaustion and emotional impairment). Physicians are like nurses in exhaustion but show greater variability in mental distance. Other staff report consistently lower burnout scores across dimensions.

3.3. Psychosocial Risk Factors Among Healthcare Professionals

Descriptive statistics for the INSAT_ERPS subscales are presented in Table 2. The results of the total sample indicate that, on average, participants reported medium levels of psychosocial risk across most categories. The highest mean scores were observed for Emotional Demands and Work Intensity, both above the medium-risk threshold. Work Values, Working Hours, and Employment Relations also fell within the medium-risk range. Conversely, Lack of Autonomy and Work Relations reflected comparatively low levels of reported risk. When analyzing the results by professional category, physicians and nurses reported the highest average scores across most dimensions. Other health professionals generally presented lower mean scores across dimensions.

3.3. Predictive Role of Work-Related Psychosocial Risk on Burnout

Pearson’s correlations indicated positive and statistically significant correlations between Exhaustion assessed through the BAT and all dimensions of the INSAT (p < 0.001). Correlations ranged from r = 0.307 to r = 0.561, suggesting moderate to strong associations. The strongest associations were observed between exhaustion and Emotional Demands (r = 0.561) as well as Work Values (r = 0.552), followed by Working Hours (r = 0.523) and Work Relations (r = 0.492).

A multiple linear regression analysis was conducted to examine the extent to which the seven INSAT dimensions predicted exhaustion. The overall model was statistically significant, F(7,146) = 16.51, p < 0.001, explaining 44.2% of the variance in exhaustion (R² = 0.442; adjusted R² = 0.415). The Durbin–Watson statistic (1.80) indicated independence of residuals and satisfactory model fit. Among the predictors included, Working Hours (β = 0.312, t(146) = 3.60, p < 0.001), Work Relations (β = 0.196, t(146) = 2.25, p = 0.026), and Emotional Demands (β = 0.295, t(146) = 3.15, p = 0.002) showed significant effects. The remaining predictors (Work Intensity, Lack of Autonomy, Employment Relations, and Work Values) did not reach statistical significance (p > 0.05) when controlling for the other variables.

The results of the multiple linear regression analysis are presented in Table 3, indicated positive and statistically significant correlations between Exhaustion assessed through the BAT and all dimensions of the INSAT (p < 0.001).

Pearson’s correlations indicated positive and statistically significant associations between Mental distance and all dimensions of the INSAT (p < 0.001). Correlations ranged from r = 0.220 to r = 0.534, suggesting moderate associations. The strongest correlations were observed between Mental distance and Work Values (r = 0.534) as well as Emotional Demands (r = 0.488), followed by Lack of Autonomy (r = 0.428) and Work Relations (r = 0.412).

The multiple linear regression analysis conducted to examine the extent to which the seven INSAT dimensions predicted mental distance was statistically significant, F(7,146) = 11.65, p < 0.001, explaining 35.8% of the variance in mental distance (R² = 0.358; adjusted R² = 0.328). The Durbin–Watson statistic (1.70) indicated independence of residuals and satisfactory model fit. Among the predictors included Work Intensity (β = −0.193, t(146) = −1.99, p = 0.049), Emotional Demands (β = 0.294, t(146) = 2.93, p = 0.004), and Work Values (β = 0.348, t(146) = 2.98, p = 0.003) showed significant effects. The remaining predictors (Working Hours, Lack of Autonomy, Work Relations, and Employment Relations) did not reach statistical significance (p > 0.05) when controlling for the other variables. The results of the multiple linear regression analysis are presented in Table 4.

Pearson’s correlations indicated positive and statistically significant associations between Cognitive impairment and all dimensions of the INSAT (p < 0.001). Correlations ranged from r = 0.332 to r = 0.520, suggesting moderate to strong associations. The strongest correlations were observed between Cognitive impairment and Work Values (r = 0.520), followed by Work Intensity (r = 0.486), Working Hours (r = 0.470), and Emotional Demands (r = 0.454).

The multiple linear regression analysis conducted to examine the extent to which the seven INSAT dimensions predicted cognitive impairment was statistically significant, F(7,146) = 11.48, p < 0.001, explaining 35.5% of the variance in cognitive impairment (R² = 0.355; adjusted R² = 0.324). The Durbin–Watson statistic (1.96) indicated independence of residuals and satisfactory model fit. Among the predictors, Work Values (β = 0.240, t(146) = 2.05, p = 0.042) emerged as the only significant positive predictor of cognitive impairment. The results of the multiple linear regression analysis are presented in Table 5.

Pearson’s correlations indicated positive and statistically significant associations between Emotional impairment and all dimensions of the INSAT (p < 0.001). Correlations ranged from r = 0.308 to r = 0.411, suggesting small to moderate relationships. The strongest associations were observed between emotional impairment and Work Relations (r = 0.411), followed by Working Hours (r = 0.380), and Work Values (r = 0.396), and Emotional Demands (r = 0.378).

The multiple linear regression analysis conducted to examine the extent to which the seven INSAT dimensions predicted emotional impairment was statistically significant, F (7,146) = 7.34, p < 0.001, explaining 26.0% of the variance in emotional impairment (R² = 0.260; adjusted R² = 0.225). The Durbin–Watson statistic (1.60) indicated independence of residuals and acceptable model fit. Among the predictors, Employment Relations (β = 0.182, t (146) = 2.10, p = 0.038) was the only significant predictor of emotional impairment. The results of the multiple linear regression analysis are presented in Table 6.

4. Discussion

Burnout is a reaction to ongoing workplace stress that can develop into a syndrome marked by depersonalization, diminished sense of personal accomplishment, and emotional tiredness [47,48]. In fact, healthcare workers who experienced burnout are in a state of physical and/or psychological tiredness that is characterised by emotional exhausting, dehumanising and cold attitudes, cynical and detached behaviour, feelings of incompetence, and demotivation in the workplace. The psychological effects of burnout syndrome include deterioration of cognitive, emotional, and attitude traits, as well as antagonistic actions towards one’s professional identity, coworkers, clients, and workplace [49,50,51,52].

Exploring psychosocial risks is essential for understanding and mitigating burnout in the workplace. These risks, such as excessive workload, poor social support, and emotional demands, are consistently linked to the development of burnout symptoms, including exhaustion, mental distance, cognitive impairment, and emotional impairment [5,40].

Exhaustion, recognized as a central dimension of burnout, is strongly influenced by a combination of organizational and interpersonal workplace factors. The results showed that the most robust predictors of exhaustion were working hours (β = 0.312; p < 0.001) and emotional demands (β = 0.295; p = 0.002), while work social relations also contributed significantly (β = 0.196; p = 0.026). These findings underscore the multifaceted nature of exhaustion, which arises not only from workload intensity but also from the emotional and social relations in the workplace.

Prolonged working hours have consistently been linked to higher exhaustion levels. Healthcare professionals working more than 40 hours per week—often under irregular or extended schedules—report significantly higher burnout scores, particularly in the domain of emotional exhaustion [53,54]. This situation limits the chances for psychological detachment and recovery, two key mechanisms for maintaining wellbeing. In healthcare settings, long hours are frequently compounded by emotional demands, which refer to the sustained psychological effort required to manage one’s emotions during patient interactions. These demands include carrying hard news, maintaining behaviour in high-stress situations, and expressing empathy under pressure lead to deeper physical and emotional fatigue, especially when emotional regulation is performed without adequate support [55,56]. In fact, poor work social relations—characterized by low interpersonal trust, lack of collaboration, and support—can exacerbate exhaustion. When employees feel isolated or undervalued, their capacity to cope with emotional and workload stressors diminishes. Conceição and Palma-Moreira [57] emphasize that rigid work environment and poor interpersonal dynamics heighten emotional strain, making employees more vulnerable to burnout. Similarly, Wekenborg et al. [58] found that individuals experiencing burnout show impaired social decision-making and reduced prosocial behavior, which undermines team cohesion and weakens collective support.

Together, these factors interact in a complex way to cause fatigue in healthcare settings: long hours can amplify the impact of emotional demands, especially when social support is weak. In fact, poor social relations reduce resilience and increase emotional dysregulation, accelerating exhaustion [59]. In addition, making organizational adjustments to workload and scheduling, addresses to a more focused interventions to improve relationships at work and provide emotional support, and promote wellbeing.

Mental distance is a core dimension of burnout characterized by a sense of alienation from one’s work, a loss of enthusiasm, and a psychological detachment from it. Our results showed that the strongest predictors of mental distance were work values (β = 0.348; p = 0.003) and emotional demands (β = 0.294; p = 0.004).

Work values emerge as significant predictors of burnout, highlighting the psychological strain resulting from the misalignment between personal values and organisational demands. When their work lacks personal purpose or conflicts with their own ideals, especially in emotionally demanding professions, this discrepancy causes an emotional retreat and a hard internal conflict. These feelings of disengagement emerges when organizational demands are in conflict with ethical or personal values of the worker; and can be seen as a self-defence strategy, as a form of self-protective emotional detachment (34). This burnout dimension is very relevant and can have hard consequences on healthcare workers wellbeing. Typically accompanied by high emotional demands, mental distance can have profound consequences on both individual health and organizational effectiveness, leading to reduced empathy, impaired decision-making, and diminished quality of care [55]. In fact, this detachment is closely linked to cynicism, a burnout dimension characterized by negative attitudes toward one’s job, colleagues or organization, but is a form of psychological withdrawal, where employees emotionally disconnect from their work to cope with stressors [60].

In the context of burnout, cognitive impairment embraces issues linked to cognitive and executive functioning, namely memory, attention, and decision-making. It is a fundamental dimension of burnout that impacts both quality of life and professional effectiveness. In our study cognitive impairment was linked to work values (β = 0.240; p = 0.042). This psychosocial risk factor is a significant predictor of burnout that can be found when employees are compelled to work in settings where the organisational culture contradicts their core work values, leading to internal conflict, and a gradual deterioration of professional identity.

Also found in mental distance, this internal conflict can exacerbate these cognitive impairments by increasing psychological strain, reducing cognitive resources and cognitive decline (Renaud & Lacroix [61]; Koutsimani et al. [62]. In a systematic review, Bufano et al. [63] came to the conclusion that psychosocial risk factors had a significant impact on cognitive functioning. They found that cognitive tiredness and decreased mental flexibility were significantly predicted by limited job control and poor value alignment. In healthcare workers we can find that work values incongruence between healthcare workers and institutional priorities, such as giving efficiency precedence over patient care and safety, contributes significantly to emotional exhaustion, inability to make decisions and depersonalization (Montgomery et al., 2019).

Emotional impairment in burnout refers to diminished emotional regulation, increased irritability, and difficulty managing interpersonal interactions. Particularly in occupations requiring intense emotional interactions, such as healthcare workers, it frequently shows up as emotional tiredness, detachment, and less empathy. In our study emotional impairment was linked to employment relations (β = 0.182; p = 0.038), that includes organizational procedures and norms, leadership management that characterized the culture of work context. In fact, mechanisms of employment relations like rigid or unsupportive employment structures, lack autonomy or low recognition and trust, increases vulnerability that can lead to emotional dysregulation, chronic emotional strain and burnout cynicism behaviours Chen et al. [55]; Conceição & Palma-Moreira [57]. Moreover, they validate the detrimental impact of poor employment relationships on emotional and psychological well-being, in line with the framework proposed by Maslach and Leiter [48].

Findings underscore a crucial understanding: the development of burnout is not solely determined by the workload intensity, or the number of hours worked. Instead, this study reveals that the quality of working life and the dynamics within the workplace play pivotal roles in predicting burnout.

Moreover, they are consistent with the Job Demands–Resources Theory: disengagement and cognitive/emotional functioning are shaped by person–job mismatch and organisational fairness, respectively, while quantitative and emotional demands exhaust resources [22]. In fact, burnout is not just an individual issue but a systemic one. Poor organizational culture—marked by distrust, lack of recognition, and inadequate communication—was linked to emotional detachment and reduced empathy among healthcare staff [63].

Evidence suggests that interventions can indeed make a positive difference. According to a recent systematic review of intervention studies [64], initiatives aimed at enhancing the well-being of healthcare workers frequently resulted in notable decreases in staff levels of burnout, stress, anxiety, and depression as well as notable improvements in resilience, work engagement, well-being, and quality of life. However, the majority of interventions were secondary-level (helping individuals manage stress and other individual strategies), and a smaller number were primary-level interventions (proactive steps by organizations to eliminate sources of stress, such as workflow changes or better staffing) [65]. This suggests that while we have a toolkit of potentially helpful strategies, more rigorous research and comprehensive programs are needed to fully address the burnout crisis, centered on work activity and psychosocial risk factors, through a holistic well-being approach.

In fact, work organization influence the level of burnout of healthcare workers: task-related risk factors include not having enough time to finish a task, workflow interruptions happening too often, not having enough or clear information, and contradictory demands between strict deadlines and the requirement to maintain high quality [5,7,66]. However, work environment characteristics, such social work relations, employment relations and emotional demands significantly impact burnout levels. Difficult interpersonal relationships, insufficient organizational support, and ongoing emotional stress all contribute to higher psychological distress and more vulnerable to burnout symptoms among healthcare workers.

5. Conclusions

This work contributes to the expanding body of knowledge in occupational health by by highlighting the important impact of psychosocial risk factors on the onset of burnout and outlines the primary predictive determinants of burnout. It is essential to explore intervention strategies that companies can implement to mitigate these risks and underscores the importance of proactive planning approach. Such strategies should focus on fostering a work environment conducive to professional fulfilment and well-being, promoting high-quality social support, employment relations, supportive leadership and peer collaboration. A comprehensive approach is necessary to address burnout, incorporating organisational changes that prioritise psychological health and well-being.