The Psychosocial Work Environment and Stress Management across X, Y, Z and babyboom generations

El entorno psicosocial laboral y la gestión del estrés en las generaciones X, Y, Z y Baby Boom

Inês Isabel dos Santos Sanlez Barata
Tânia Gaspar
Lusofona University, SPIC, HEI-LAB, Lisbon, Portugal

VOL. 51. Número 188 (2025)

ISSN 0211-7339
http://dx.doi.org/10.33776/EUHU/amc.v51i188.9134

Abstract:

Healthy work environments reduce risks and enhance employee performance and satisfaction, while stress can harm their health and engagement. Each generation has its own experiences and expectations that should be considered. This study explores the relationship between the psychosocial work environment and stress management according to generation, through a cross-sectional, comparative, and quantitative study. The study sample consisted of 4551 participants, 2189 belonging to Generation X, 1657 to Generation Y, 383 to Baby Boomers and 317 to Generation Z. Participants were recruited through convenience sampling and included volunteers aged 18 or older who work in Portugal. The results reveal the existence of differences in stress management across generations, however Baby Boomers tend to highlight similar factors to Generation X for work stress management, just as Generation Y and Generation Z tend to highlight similar factors. Leadership can influence worker stress, so they should consider their needs.

Keywords:

Psychosocial environment; leadership; work; stress; generations

Resumen:

Los ambientes de trabajo saludables reducen riesgos y potencian el desempeño y la satisfacción de los trabajadores, y el estrés puede perjudicar su salud y compromiso. Cada generación tiene experiencias y expectativas propias que deben ser consideradas. Este estudio explora la relación entre el ambiente psicosocial laboral y la gestión del estrés según la generación, mediante un estudio transversal, comparativo y cuantitativo. La muestra estuvo compuesta por 4.551 participantes: 2.189 pertenecientes a la Generación X, 1.657 a la Generación Y, 383 Baby Boomers y 317 a la Generación Z. Los participantes fueron reclutados mediante muestreo por conveniencia e incluyeron voluntarios de al menos 18 años que trabajan en Portugal. Los resultados indican diferencias generacionales en las formas de gestionar el estrés. En particular, los Baby Boomers y la Generación X comparten preocupaciones similares relacionadas con el estrés laboral, mientras que la Generación Y y la Generación Z tienden a destacar factores similares entre sí. Las lideranzas pueden influir en el estrés de los trabajadores, por lo que deben considerar sus necesidades.

Palabras claves:

Entorno psicosocial; liderazgo; trabajo; estrés; generaciones

Fecha de recepción: 28 de julio de 2025
Fecha de aceptación: 6 de octubre de 2025

Correspondencia: Tania Gaspar, PhD, Lusófona University/Hei-Lab/; CHRC/ Lisbon NOVA UniversityCampo Grande, Lisbon, Portugal. E-mail: tania.gaspar@ulusofona.pt

Introduction

Psychosocial Work Environment

The World Health Organization (WHO) model for Healthy Workplaces suggests that a healthy workplace involves collaboration between workers and managers to foster a continuous improvement process aimed at protecting and promoting the health, safety, and well-being of all workers, as well as ensuring the sustainability of the workplace. This model considers the fundamental parameters of the physical and psychosocial work environment, personal health resources at the workplace, and the organization’s involvement in the community (Burton, 2010).

The psychosocial work environment can be considered a concept that links economic, social, and political structures to health and illness through psychological and psychophysiological processes. It integrates the individual’s experience and interaction with the environment, as well as the structural factors of the context. Although various factors contribute to the mental health and well-being of workers, the workplace environment plays a predominant role. In a positive psychosocial environment, work can benefit workers’ mental health as well as their quality of life, contributing to social inclusion, identity, and increased self-confidence (Pereira et al., 2020; Rugulies, 2019).

Psychosocial factors include aspects of the work and its environment (e.g., organizational culture, job roles, interpersonal relationships at work, content and meaning of tasks), aspects of the extra-organizational environment (e.g., household tasks), and personal aspects (e.g., personality, attitudes) (Bonsaksen et al., 2021; Burton, 2010; Gaspar et al., 2022; Martinez & Fischer, 2019; Pereira et al., 2020; Rugulies, 2019; Stobiecka & Pangsy-Kania, 2021; Varianou-Mikellidou et al., 2020), which generate cognitive and emotional processes that lead to psychophysiological and behavioral reactions, impacting the risk of developing somatic diseases and mental disorders (Pereira et al., 2020; Rugulies, 2019). The psychosocial working conditions influence the cognitions, emotions, behaviors, and physiology of workers, just as these processes also alter the way in which workers experience their own working conditions (Bonsaksen et al., 2021; Rugulies, 2019; Stobiecka & Pangsy-Kania, 2021).

The promotion of mental health and the prevention of associated issues are based on the identification of personal, community, and socioeconomic factors, with the aim of intervening in the reduction of risks and the enhancement of existing strengths (Eriksson et al., 2018). Strategies for promoting and protecting mental health at work include strengthening the ability to recognize and take action on mental health conditions in the workplace, especially for individuals in leadership positions (Pereira et al., 2020).

Leaders’ behavior should take into account certain personal values, through the adoption of social and organizational principles that are considered more sustainable in terms of human nature and systems. Among other aspects, the relationship between workers and their supervisors involves the monitoring of time, tasks, and goals. In this regard, workers should be involved in work planning, as they are the ones who experience the work reality and its health-related consequences, in order to foster feelings of belonging and appreciation, thereby minimizing, among other adverse consequences, the sense of excessive control (Berge & Berge, 2019; Črešnar & Nedelko, 2020; Gaidhani & Sharma, 2019; Kim, 2021; Pereira et al., 2020).

Work engagement can be considered the worker’s commitment regarding their emotional and behavioral contribution toward the goals set by the organization. This factor of the psychosocial work environment is influenced by leadership attitudes and behaviors, serving as an individual resource that impacts the success of teams, both positively and negatively, as well as the organizations to which they belong (Bonsaksen et al., 2021; Dåderman et al., 2023). Effective training, proper worker selection, reward systems, and the sharing of information and ideas can influence professionals’ engagement (Lee et al., 2024). Positive worker engagement tends to contribute to the reduction of their stress levels (Kim, 2021; Patro & Kumar, 2019).

Psychosocial Work Environment and Professional Stress Management

Work-related stress, or occupational stress, is a psychophysiological reaction that occurs when an individual perceives that job demands exceed their ability to cope, representing a consequence of a negative psychosocial work environment when it surpasses healthy limits (Gaspar et al., 2023a; Kim, 2021; Lu et al., 2021; Nanda et al., 2020; Patro & Kumar, 2019). Occupational stress can also be experienced when demands and expectations regarding performance are minimal or entirely absent (Gaspar et al, 2024).

A prolonged period of work-related stress can lead to both mental and physical health problems. Stress affects workers psychologically, emotionally, and behaviorally, and may be directly linked to health issues such as coronary diseases, headaches, anxiety, and depression. It is also one of the main factors impacting employee engagement. Stress can undermine organizational performance, individual worker performance, and the overall quality of work produced (Gabriel & Aguinis, 2022; Kim, 2021; Patro & Kumar, 2019; Sharma, 2023). Long working hours, adaptation to new technologies, role overload (i.e., an imbalance between the amount of work and the time available to complete it), role ambiguity (i.e., performing tasks without clear and specific information), poor workplace relationships, unjustified performance evaluations, and lack of career advancement opportunities are all variables that contribute to the intensification of employee stress (Kim, 2021; Sharma, 2023; Stobiecka & Pangsy-Kania, 2021).

Workplace relationships are crucial for fostering a positive psychosocial work environment, particularly the relationship between employees and their leaders. Skills associated with effective and positive leadership can be developed and have the potential to mitigate work-related stress. Leaders should serve as role models for professional conduct, encouraging employees to strive toward realizing their full potential and to take responsibility for their work (Kim, 2021; Sharma, 2023).

Work relationships characterized by hostility tend to increase stress levels. Therefore, it is essential to adopt effective communication in order to minimize feelings of distrust and confusion and to enhance employee commitment. Flexible working hours can also be beneficial in reducing stress, as they allow individuals to manage their personal and professional lives according to their needs. Ensuring that employees have access to clear goals, as well as appropriate training and experience, is another measure that can be implemented to avoid ambiguity in the effective performance of their duties and, consequently, to reduce stress levels (Kim, 2021; Sharma, 2023).

Stress management becomes a fundamental issue for both employees and the organizations to which they belong, as the implementation of stress management programs enhances performance and improves the quality of the work produced. Managing stress involves understanding that individuals are exposed to stress-inducing agents (Gaspar et al., 2023a; 2024; Kim, 2021; Patro & Kumar, 2019) and that the way a person adapts to a given situation is influenced by the coping strategies they possess prior to the stress-inducing event, as well as by the demands imposed by that situation (DGS, 2021; Kim, 2021; Lu et al., 2021; Nanda et al., 2020; Patro & Kumar, 2019).

Nevertheless, there are strategies that organizations can adopt. Stress levels can be minimized if organizations are receptive to employees’ ideas and provide opportunities to guide and involve them in decision-making processes. When individuals feel they are being treated unfairly, they tend to be less productive. Conversely, when they are actively involved in the organization’s decision-making processes, they are more likely to exert greater effort toward achieving better organizational outcomes. Employee engagement is particularly important for effective stress management, as consulting workers helps leaders foster a climate of trust. Involving employees in the development of preventive measures enhances the organizational climate and increases the effectiveness of the measures implemented (Kim, 2021; Patro & Kumar, 2019).

Psychosocial Work Environment and Stress Management Among Professionals Across Generations

It’s possible to categorize generational groups based on shared characteristics such as birth years and the historical, technological, and social contexts experienced throughout their development, which contribute to the formation of similar values, attitudes, and behaviors among their members. The literature commonly identifies four generations of professionals: Baby Boomers (BB), Generation X (GX), Generation Y (GY), and Generation Z (GZ) (Berge & Berge, 2019; Gaidhani & Sharma, 2019; Younas & Bari, 2020). Each generation experiences particular events that shape distinct preferences, expectations, beliefs, and work styles (Gaidhani & Sharma, 2019; Younas & Bari, 2020).

The perception and experience of the psychosocial work environment can vary significantly among members of different generations, which impacts how stress is managed by professionals. Leadership style and the level of employee engagement can influence how workers from different generations interpret stress and develop coping strategies (DGS, 2021), Therefore, understanding these relationships is essential for effective intervention in clinical and health psychology. By taking into account the generational characteristics of their professionals, organizations foster feelings of belonging and engagement among employees, demonstrating their openness to workers’ ideas (Krisdayanti & Lianto, 2023).

BB (1946-1964) tend to value job stability, loyalty, clear hierarchical structures, and dedication to their roles (Berge & Berge, 2019; Gaidhani & Sharma, 2019; Jung & Yoon, 2021; Younas & Bari, 2020). Adapting to new technologies, the pressure to keep up with constant changes in the labor market, significant shifts in leadership that affect trust relationships, and the lack of recognition for their work can all be sources of stress for members of this generation. Planning and work organization are strategies they commonly use for managing stress (Miteva et al., 2024; Spiess et al., 2021).

GX (1965-1980) values autonomy and the establishment of a balance between personal and professional life, emphasizing the need to prioritize multiple life domains beyond the workplace. As such, flexibility is considered a fundamental value (Berge & Berge, 2019; Gaidhani & Sharma, 2019; Jung & Yoon, 2021; Younas & Bari, 2020). This balance has a significant impact on employee engagement, performance, and satisfaction, as it fosters the development of a positive and mutually reinforcing relationship with the workplace (Krisdayanti & Lianto, 2023). Rigid environments and work overload, particularly when they interfere with family responsibilities, can generate stress in these professionals, who tend to resort to stress management strategies such as task delegation and time management (Miteva et al., 2024; Pasla et al., 2021; Standifer & Lester, 2020).

GY (1981-1996) tends to value innovation, collaboration, and work purpose, preferring workplaces that offer opportunities for continuous development and intrinsic aspects that foster their engagement (e.g., the possibility of applying their diverse knowledge in the job) (Berge & Berge, 2019; Gaidhani & Sharma, 2019; García et al., 2019; Jung & Yoon, 2021; Younas & Bari, 2020). Members of this generational group tend to be focused on problem-solving, with a high capacity for adapting to new challenges (Stobiecka & Pangsy-Kania, 2021). Inadequate feedback, lack of work purpose, and limited opportunities for personal and professional development and growth, rigid structures, the pursuit of immediate recognition, and constant comparison on social media are stress factors for these individuals. Stress management strategies tend to involve mindfulness practices, well-being-promoting activities (e.g., physical exercise, hobbies), and online support groups (Cvenkel, 2020; Lestari & Margaretha, 2021; Miteva et al., 2024; Oksa et al., 2021).

GZ (1997-2010) can be characterized by the value placed on inclusion, diversity, and flexibility in the workplace (Berge & Berge, 2019; Gaidhani & Sharma, 2019; Jung & Yoon, 2021; Lee et al., 2024; Younas & Bari, 2020). These professionals tend to choose jobs that align with their needs and focus on success, establishing vague boundaries between work and leisure time (Stobiecka & Pangsy-Kania, 2021). The lack of flexibility, technological support, and inclusion policies, as well as insecurity about their professional future and the demand for rapid adaptation, can cause stress among members of GZ. Given that technology has been part of their lives since birth, these workers tend to resort to stress management strategies that are characterized by speed and practicality, such as meditation apps, online therapy sessions, and using social media as a means of emotional expression (Borg et al., 2020; Krisdayanti & Lianto, 2023; Miteva et al., 2024; Sakroni, 2024).

Despite the identified differences, it may also be relevant to emphasize the common factors among the groups in order to address the challenges related to diversity in the workplace. Regarding the work context, the values that tend to converge across generations include variables of the psychosocial work environment that contribute to a healthy work environment (e.g., communication, respect, engagement, recognition, trust in leaders and other team members) (Berge & Berge, 2019).

In this regard, the main objective of the present study is to examine the relationship between the psychosocial work environment and stress management among professionals, considering the generation to which they belong.

Method

Design and Participants

A cross-sectional and comparative study was conducted using a quantitative methodology. Participants were recruited through convenience sampling. Only professionals who voluntarily agreed to participate in the study, were at least 18 years old, and were employed in Portugal were included. The study involved a total of 4551 participants, 64% female (n=2912) and 36% male (n=1636). The age of the participants ranged from 18 to 73 years (M = 44.79; SD =10.80). The majority of participants (48.2%) belonged to GX (n=2189), 36.4% to GY (n=1657), 8.4% to BB (n= 383) and 7% to GZ (n=317).

Instruments

The instrument used was the Healthy Workplaces Ecosystem (EATS), consisting of 62 items organized into 9 dimensions, based on the conceptual model of Healthy Workplaces proposed by the WHO (Burton, 2010). The Ethics and Values dimension includes 8 items (e.g., “The organization focuses on the well-being of employees and has policies and strategies to promote it”), the Leadership Commitment dimension contains 6 items (e.g., “Leadership is characterized by guidance, facilitation, and encouragement”), the Employee Engagement dimension consists of 7 items (e.g., “I feel motivated and enjoy doing my job”), the Psychosocial Work Environment related to Content and Relationship with Leadership includes 12 items (e.g., “My direct supervisor values my job satisfaction”), the Psychosocial Work Risks related to Well-being and Mental Health includes 5 items (e.g., “In the past 4 weeks, I have felt sad”), the Physical Environment consists of 5 items (e.g., “I believe that the conditions of the facilities and equipment are adequate for me to perform my work safely”), the Teleworking dimension has 3 items (e.g., “When working from home, I am better able to manage my work schedule”), the Community Engagement dimension includes 12 items (e.g., “The organization considers the interests of future generations in its development plans”), and the Personal Health Resources dimension contains 4 items (e.g., “The organization offers and/or facilitates access to health services (consultations, treatments, and medications)”). All items use a 5-point Likert scale, where 1 means “strongly disagree” and 5 means “strongly agree.” The higher the score, the more positive the participant’s perception of the domain being analyzed, except for the Psychosocial Work Risks related to Well-being and Mental Health dimension, where a higher score reflects a more negative perception (Gaspar et al., 2022). The Cronbach’s alpha values obtained for each factor show that they have adequate internal consistency (ranging from 0.82 to 0.95) (DeVellis, 2017; Gaspar et al., 2022; George & Mallery, 2003).

Considering the objective of the study, only 4 dimensions were taken into account: Leadership Commitment; Employee Engagement; Psychosocial Work Environment related to Content and Relationship with Leadership; Psychosocial Work Risks related to Well-being and Mental Health. The Cronbach’s alpha values obtained for each factor show that they maintain adequate internal consistency (ranging from 0.88 to 0.95) (DeVellis, 2017; George & Mallery, 2003).

Procedure

The study was submitted and approved by the ethics committee of the Prof. Fernando

Fonseca Hospital (reference 031/2021) and was subsequently presented to the Ethics and Deontology Committee for Scientific Research (CEDIC).

Data collection was conducted between October 2023 and March 2024. Public, private, and social organizations, as well as individuals independent of any organization, were invited to participate. Organizations from different sizes, sectors of activity, and national regions were contacted. Participants were recruited using a convenience sampling method. Organizations that agreed to participate received the questionnaire through a link for internal dissemination among their employees. The link provided access to information about the scope and purpose of the study, contact details for any additional questions, and information regarding confidentiality, anonymity, and the voluntary nature of participation. Participants could only access the questionnaire after providing their favorable consent via the informed consent form. If they disagreed with the presented conditions, they were unable to begin completing the questionnaire. The questionnaire was administered through an online platform and could be completed on any electronic device with internet access (e.g., computer, tablet, smartphone) and in any environment conducive to the participant’s concentration. The average response time was 12 minutes. Participants were given the option to withdraw at any time before submitting the questionnaire.

Data analysis was performed using the IBM SPSS Statistics 27 software. Descriptive statistics were analyzed to characterize the demographic profile of the study participants (i.e., sex, age, marital status, education level, employment status, organization location and size, and sector of activity).

To proceed with the group comparisons, the Wilcoxon-Mann-Whitney test was performed for sex, marital status, education level, employment status, and organization size, and the Kruskal-Wallis test was used for generation, as the assumptions for parametric tests were not met (Fife-Schaw, 2006). The Spearman Correlation Coefficient was used to analyze the association between the variables under study, as the assumptions for the use of parametric tests were not met (Fife-Schaw, 2006). Finally, four Multiple Linear Regressions were conducted to gain a deeper understanding of the relationship between the psychosocial work environment (specifically, leadership and employee engagement) and stress management among professionals, taking into account their generation (Marôco, 2021).

Results

Descriptive Statistics

The results obtained for marital status revealed that 39.4% of the participants are single (n=1793) and 60.6% are not single (n=2758). In terms of education, 35.9% of the participants completed compulsory education (n=1615) and 64.1% have completed more than compulsory education (n=2887).

Regarding professional status, 60.1% of participants are in a situation of job stability (n=2659) and 39.9% in a situation of job instability (n=1762). The majority of participants (55.3%) work in an organization located in the Lisbon metropolitan area (n=2516), 25.7% in the Porto metropolitan area (n=1168), 8.8% in the central region (n=402), 4% in Alentejo (n=181), 3.1% in the northern region (n=142), 2.5% in the autonomous region of the Azores (n=113), 0.4% in the Algarve (n=20), and 0.1% in the autonomous region of Madeira (n=4). Most participants (92.2%) work in a national organization (n=3765) and 7.8% in a multinational organization (n=317).

Regarding the sector of activity, 38.8% of participants work in human health activities (n=1761), 22.2% in municipalities (n=1008), 8.7% in education (n=395), 5.9% in wholesale and retail trade (n=270), 3.9% in social support activities (n=179), 2% in transport and storage (n=91), 1.8% in financial and insurance activities (n=80), 0.3% in accommodation, food services, and similar (n=13), 0.3% in manufacturing industries (n=12), 0.2% in agriculture, animal production, hunting, forestry, and fishing (n=9), 0.2% in construction (n=9), 0.2% in electricity, gas, and water (n=7), 0.1% in real estate activities (n=5), and 15.5% in other sectors (n=704). Regarding the size of the organization, 86% of participants work in a large company or organization (n=3839), and 14% work in a micro, small, or medium-sized company or organization (n=625).

Reliability Statistics – Cronbach’s Alpha

The Cronbach’s alpha coefficients obtained for each dimension under investigation indicate that the internal consistency remains robust (DeVellis, 2017; George & Mallery, 2003) (Table 1).

Group Comparisons

The Wilcoxon-Mann-Whitney test revealed statistically significant differences between the groups of the Sex variable for Worker Engagement (U=1961403.000; p <.001), Psychosocial Work Environment related to Content and Leadership Relationship (U=1992009.500; p <.001), and Psychosocial Work Risks related to Well-being and Mental Health (U=2164512.000; p <.001). Female participants exhibited higher scores for Worker Engagement (= 3.71; = 3.43), Psychosocial Work Environment related to Content and Leadership Relationship (= 3.75; = 3.58), and Psychosocial Work Risks related to Well-being and Mental Health (= 3.00; = 2.80) (Table 2).

The Wilcoxon-Mann-Whitney test revealed statistically significant differences between the groups of the Marital Status variable for Stress Management (U=2306791.000; p <.001), with higher scores for participants who are not single (= 3.25; = 3.50), and for Psychosocial Work Risks related to Well-being and Mental Health (U=2374680.000; p =.034), although the medians do not reflect these differences (= 3.00; = 3.00) (Table 2).

The Wilcoxon-Mann-Whitney test revealed statistically significant differences between the groups of the Education variable for Leadership Commitment (U=2086705.000; p <.001), Worker Engagement (U=2179008.500; p <.001), and Psychosocial Work Environment related to Content and Relationship with Leadership (U=2221172.000; p =.014). Participants who completed only mandatory education had higher scores for Leadership Commitment ( = 3.33; = 3.17), Worker Engagement ( = 3.71; = 3.57), and Psychosocial Work Environment related to Content and Relationship with Leadership (= 3.75; = 3.67) (Table 2).

The Wilcoxon-Mann-Whitney test revealed statistically significant differences between the groups of the Employment Status variable for Leadership Commitment (U=2154027.000; p <.001), with higher scores reported by participants in an unstable employment situation (= 3.17; = 3.33), and for Psychosocial Work Risks related to Well-Being and Mental Health (U=2172755.500; p <.001), with higher scores among those in a stable employment situation (= 3.00; = 2.80) (Table 2).

The Wilcoxon-Mann-Whitney test revealed statistically significant differences between the groups of the Organization Size variable for Leadership Commitment (U=889033.000; p <.001), Worker Engagement (U=924198.000; p <.001), and the Psychosocial Work Environment related to Job Content and Leadership Relationship (U=861140.000; p <.001). Participants working in micro, small, or medium-sized companies or organizations reported higher scores in Leadership Commitment ( = 3.83; = 3.17), Worker Engagement ( = 3.86; = 3.57), and Psychosocial Work Environment related to Job Content and Leadership Relationship (= 3.92; = 3.58). Statistically significant differences were also observed for Stress Management (U=1113990.000; p =.005), although the median scores did not reflect these differences (= 3.50; = 3.50) (Table 2).

The Kruskal-Wallis Test revealed statistically significant differences between generational groups for Stress Management (H(3)=60.760; p <.001), Leadership Commitment (H(3)= 41.456; p <.001), Employee Engagement (H(3)=28.645; p <.001), Psychosocial Work Environment Related to Work Content and Leadership Relationship (H(3)= 21.765; p <.001), and Psychosocial Work Risks Related to Well-Being and Mental Health (H(3)=24.032; p <.001). Regarding Stress Management, BB reported the highest scores (Med=3.75), followed by GX (Med=3.50), and GY (Med=3.25) and GZ (Med=3.25). For Leadership Commitment, GZ had the highest scores (Med=3.67), followed by BB (Med=3.17), GX (Med=3.17), and GY (Med=3.17). In terms of Employee Engagement, BB, GX, and GZ all reported higher scores (Med=3.71), compared to GY (Med=3.57). Regarding the Psychosocial Work Environment Related to Work Content and Leadership Relationship, GZ had the highest scores (Med=3.92), followed by BB (Med=3.67), GX (Med=3.67), and GY (Med =3.67). As for Psychosocial Work Risks Related to Well-Being and Mental Health, GX and GY scored higher (Med=3.00), while BB and GZ had lower scores (Med=2.80) (Table 3).

Correlations

All correlations between the study variables are statistically significant, with a particularly strong correlation observed between Worker Involvement and the Psychosocial Work Environment related to Job Content and Leadership Relationship (r= .735). Moderate correlations were also found between Stress Management and Worker Involvement (r= .342), Stress Management and the Psychosocial Work Environment related to Job Content and Leadership Relationship (r= .364), and Stress Management and Psychosocial Risks related to Well-being and Mental Health (r= -.415). Furthermore, moderate correlations were identified between Leadership Commitment and Worker Involvement (r= .489), Leadership Commitment and the Psychosocial Work Environment related to Job Content and Leadership Relationship (r= .596), and Leadership Commitment and Psychosocial Risks related to Well-being and Mental Health (r= -.334) (Table 4).

Multiple Linear Regressions

For BB, the results of the Multiple Linear Regression showed that the predictor variables accounted for 28.9% of the total variance in the Stress Management variable (Table 5), with the model being statistically significant (F(6,364)= 26.056; p<.001) (Table 6). The strongest predictor of stress management was Work-Related Psychosocial Risks concerning Well-Being and Mental Health (β= -.400; p<.001), followed by Psychosocial Work Environment related to Job Content and Leadership Relations (β= .213; p= .003), Worker Involvement (β= .203; p= .002), Leadership Commitment (β= -.143; p= .008), and Organizational Size (β= -.089; p= .048). Marital Status was not a significant predictor of stress management (β= .052; p= .245) (Table 7).

For GX, the results of the Multiple Linear Regression showed that the predictor variables accounted for 28.9% of the total variance in the Stress Management variable (Table 5), with the model being statistically significant (F(6,2146)= 146.747; p<.001) (Table 6). The strongest predictor of stress management was Work-Related Psychosocial Risks concerning Well-Being and Mental Health (β= -.409; p<.001), followed by Psychosocial Work Environment related to Job Content and Leadership Relations (β= .199; p<.001), Worker Involvement (β= .190; p<.001), and Leadership Commitment (β= -.074; p= .001). Marital Status (β= .019; p= .306) and Organizational Size (β= .020; p= .265) were not significant predictors of stress management (Table 7).

For GY, the results of the Multiple Linear Regression indicated that the predictor variables explained 31.8% of the total variance in the Stress Management variable (Table 5), with the model being statistically significant (F(6,1623)= 127.784; p<.001) (Table 6). The strongest predictor of stress management was Work-Related Psychosocial Risks concerning Well-Being and Mental Health (β= -.437; p<.001), followed by Worker Involvement (β= .283; p<.001), Leadership Commitment (β= -.130; p<.001), Psychosocial Work Environment related to Job Content and Leadership Relations (β= .116; p<.001), and Marital Status (β= .0.54; p= .008). Organizational Size was not a significant predictor of stress management (β= -.015; p= .481) (Table 7).

Regarding GZ, the results of the Multiple Linear Regression showed that the predictor variables explained 32.3% of the total variance in the Stress Management variable (Table 5) (F(6,292)= 24.674; p<.001) (Table 6). The strongest predictor of stress management was Work-Related Psychosocial Risks concerning Well-Being and Mental Health (β= -.481; p<.001), followed by Worker Involvement (β= .184; p=.022) and Psychosocial Work Environment related to Job Content and Leadership Relations (β= .173; p=.034). Marital Status (β= .018; p= .708), Organizational Size (β= -.010; p= .843), and Leadership Commitment (β= -.083; p= .176) were not significant predictors of stress management (Table 7).

Discussion

The aim of this study is to explore the relationship between the psychosocial work environment and stress management among professionals, considering their generational affiliation. The results corroborate the existence of generational differences in occupational stress management (Gabrielova & Buchko, 2021; Saba, 2021; Stevanin et al., 2020). BB appear to exhibit a more positive perception of their stress management competencies, followed by GX, whereas GY and GZ tend to display a more negative perception in this domain. Work experience may enhance stress management among BB, as they possess broader knowledge of the challenges and solutions that may arise in the performance of their roles, thereby fostering greater role clarity and predictability (Cvenkel, 2020). However, other factors may account for the results obtained, such as higher levels of social desirability (Kuokkanen & Sun, 2020) and lower emotional intelligence (Machová et al., 2020; Todorova, 2024), for instance. Similarly, workplaces may be poorly structured and insufficiently adapted to the needs of younger generations, which could lead them to experience greater stress and increased difficulty in managing it (Janssen & Carradini, 2021; Mahmoud et al., 2021).

The predictor that contributed most significantly to explaining stress management across all four generations was work-related psychosocial risks associated with well-being and mental health. The literature emphasizes that such psychosocial risks play a central role in fostering a healthy work environment and that their conditions directly influence professionals’ stress levels (Gabriel & Aguinis, 2022; Gaspar et al., 2023a; Lu et al., 2021). The findings further revealed that BB and GZ perceive themselves to be less exposed to psychosocial risks related to well-being and mental health, in comparison to GX and GY, who report more negative perceptions in this domain. As they approach the end of their professional careers, BB’s possess experiential knowledge not yet acquired by younger employees. The opportunity to share this expertise and mentor younger generations may reduce their perceived exposure to psychosocial risks, as it reinforces their work values (e.g., recognition) (Gaidhani & Sharma, 2019; Younas & Bari, 2020). Similarly, GZ’s emphasis on workplace inclusion and diversity may also contribute to more favorable perceptions in this area (Jung & Yoon, 2021; Lee et al., 2024).

In addition to psychosocial risks, the significant predictors of stress management for both BB and GX included the psychosocial work environment related to job content and leadership relationships, followed by employee involvement and leadership commitment. For GY and GZ, employee involvement and the psychosocial work environment related to job content and leadership relationships also emerged as relevant predictors. These findings are consistent with previous research, such as the study by Gaspar et al. (2023a), which indicates that elements of the psychosocial work environment – specifically those related to leadership relationships, autonomy, workplace recognition, and interpersonal dynamics – are closely linked to employees’ stress management. A positive psychosocial work environment encompasses effective communication, recognition, respect, fairness, development opportunities, consideration of individual needs, role clarity, and autonomy, along with factors related to well-being and mental health (e.g., stress levels, sadness, and work-life balance). A healthy work environment is characterized, among other things, by a strong focus on employee well-being and the active engagement of staff in goal-setting and decision-making processes (Bonsaksen et al., 2021; Dåderman et al., 2023). Although generational differences in work values exist, the consistent relevance of psychosocial risks, work environment, and employee involvement across all generations suggests a convergence of core work values – such as communication, respect, and employee appreciation – as proposed by Berge and Berge (2019).

Similar to BB and GX, leadership commitment was identified as a predictor of stress management for GY, which was not observed in GZ. The results revealed that GZ reports a more positive perception of leadership commitment compared to the other generational groups. This may be attributed to GZ’s stronger preference for integrating personal values into the workplace (e.g., inclusion, diversity) (Jung & Yoon, 2021; Lee et al., 2024), and their tendency to choose work environments that align with their individual needs and ideals. Consequently, they are less likely to remain in professional settings that do not reflect their values and expectations (Stobiecka & Pangsy-Kania, 2021).

Organizational size emerged as a predictor of stress management among BB. The study by Torre et al. (2024) indicated that organizational size does not directly contribute to elevated stress levels, suggesting instead that the type of activity performed may play a more significant role. Conversely, Cvenkel (2021) argues that the size of an organization affects both the scope and nature of the policies it implements, which may, in turn, influence how professionals manage stress. Considering that the findings reveal this variable to be relevant only for BB, it is plausible to hypothesize that organizational size may impact the values prioritized by this generation.

Marital status was identified as a predictor of stress management among GY. The data indicate that individuals who are not single report a more positive perception of their ability to manage stress compared to their single counterparts. Sinta and Dwiyanti (2023) emphasize the importance of partner support in managing occupational stress, noting that such support assists professionals in navigating work-related challenges. Employees with dependent children may particularly benefit from the presence of a partner, as it facilitates the management of family responsibilities. The relevance of marital status for stress management in GY may be attributed to the life stage typically associated with this cohort, during which individuals are more likely to be engaged in parenting roles (Harper & Botero-Meneses, 2022).

Conclusion

The study’s findings reveal generational differences in the management of occupational stress. While disparities were observed across all generational cohorts, BB tend to share similar stress management predictors with GX, just as GY and GZ appear to emphasize comparable factors. The results further underscore the influence of leadership-driven management policies on employees’ stress regulation, highlighting the importance of tailoring workplace practices to the distinct needs and characteristics of each generational group.

The main limitations of this study include the use of a convenience sampling method. Ideally, future research should replicate the study using a methodology that allows for the inclusion of a randomized sample. Nonetheless, the sample encompassed participants from public, private, and third-sector organizations, as well as individuals unaffiliated with any organizational structure, across various organizational sizes, sectors of activity, and national regions – enhancing the illustrative value of the sample. Additionally, although the use of self-report instruments may introduce biases such as social desirability, a validated instrument appropriate for the target population was employed, thereby mitigating this limitation.

Future studies could explore the relationship between the psychosocial work environment and stress management among professionals, considering both their generational background and the sector of activity in which they are engaged.

The relationship between the psychosocial work environment, particularly with regard to leadership and employee involvement, and stress management is influenced by generational differences. In this regard, managing the psychosocial environment and stress in the workplace must take into account the distinct characteristics and needs of each generation (Krisdayanti & Lianto, 2023). A healthy and inclusive work environment has the potential to enhance employees’ well-being, as well as increase productivity and team cohesion. Investment in this area not only protects employees’ health but also fosters a positive work environment. It’s crucial to recognize and value generational differences, adapting the policies adopted to create an environment where all employees have the opportunity to thrive (Gaspar et al., 2023b).

In terms of implications for Clinical and Health Psychology, it is noteworthy that it has been tested and proven that psychologists are able to create a climate of trust, facilitating the development of solutions and commitments to change. In this sense, knowing that stress can be managed and that leadership can influence this management, this issue should be addressed as an organizational problem, beyond just an individual one. Clinical and health psychologists play a key role in promoting health, safety, well-being, and quality of professionals, possessing tools that allow them to prevent, as well as solve, problems. Adaptation to organizational changes and the management of new challenges may include clinical and health psychology “from a positive perspective and primary prevention, focusing on strengths and opportunities, optimizing skills, promoting well-being and quality of life, and acting, preferably, before problems arise or settle in” (Matos et al., 2020). It is evident that there is a need to implement personalized interventions that take into account the specificities of each generation, in order to promote healthy work environments and enhance the management of occupational stress.

References

Berge, Z. L., & Berge, M. B. (2019). The economic abcs of educating and training generations x, y, and z. Performance Improvement, 58(5), 44-53. https://doi.org/10.1002/pfi.21864

Bonsaksen, T., Nerdrum, P., & Østertun Geirdal, A. (2021). Psychological distress and its associations with psychosocial work environment factors in four professional groups: A cross-sectional study. Nursing & Health Sciences, 23(3), 698-707.

Borg, N., Scott-Young, C. M., & Naderpajouh, N. (2020). Strategies for business sustainability in a collaborative economy: building the career resilience of generation Z. Strategies for business sustainability in a collaborative economy, 306-329. IGI Global.

Burton, J. (2010). WHO Healthy Workplace Framework and Model: Background and Supporting Literature and Practices. World Health Organization. https://apps.who.int/iris/bitstream/handle/10665/113144/9789241500241_eng.pdf

Črešnar, R., & Nedelko, Z. (2020). Understanding future leaders: How are personal values of generations Y and Z tailored to leadership in industry 4.0?. Sustainability, 12(11), 4417. https://doi.org/10.3390/su12114417

Cvenkel, N. (2020). Multigenerational workforce and well-being in the twenty-first-century workplace. Well-Being in the Workplace: Governance and Sustainability Insights to Promote Workplace Health, 191-224. Springer. https://doi.org/10.1007/978-981-15-3619-9_9

Cvenkel, N. (2021). Equilíbrio entre vida profissional e pessoal e bem-estar no trabalho: Perspectiva dos funcionários para promover um local de trabalho psicologicamente saudável. The Palgrave handbook of corporate social responsibility, 429-451. https://doi.org/10.1007/978-3-030-42465-7_19

Dåderman, A.M., Kajonius, P.J., Hallberg, A. & Hellström, A. (2023). Leading with a cool head and a warm heart: trait-based leadership resources linked to task performance, perceived stress, and work engagement. Current Psychology 42(33), 29559–29580. https://doi.org/10.1007/s12144-022-03767-8

DeVellis, R. F. (2017). Scale development: Theory and applications (4.ª ed.). SAGE.

Direção-Geral da Saúde (2021). Guia técnico n.º 3: vigilância da saúde dos trabalhadores expostos a fatores de risco psicossocial no local de trabalho. Lisboa.

Eriksson, M., Ghazinour, M., & Hammarström, A. (2018). Different uses of Bronfenbrenner’s ecological theory in public mental health research: what is their value for guiding public mental health policy and practice?. Social Theory & Health, 16, 414-433.

Fife-Schaw, C. (2006). Levels of measurement. In G. M. Breakwell, S. Hammond, C. Fife-Schaw, & J. A. Smith (Eds), Research Methods in Psychology (3.ª ed.). SAGE.

Gabriel, K. P., & Aguinis, H. (2022). How to prevent and combat employee burnout and create healthier workplaces during crises and beyond. Business horizons, 65(2), 183-192. https://doi.org/10.1016/j.bushor.2021.02.037

Gabrielova, K., & Buchko, A. A. (2021). Here comes Generation Z: Millennials as managers. Business horizons, 64(4), 489-499. https://doi.org/10.1016/j.bushor.2021.02.013

Gaidhani, S., Arora, L., & Sharma, B. K. (2019). Understanding the attitude of generation Z towards workplace. International Journal of Management, Technology and Engineering, 9(1), 2804-2812.

García, G. A., Gonzales-Miranda, D. R., Gallo, O., & Roman-Calderon, J. P. (2019). Employee involvement and job satisfaction: a tale of the millennial generation. Employee Relations: The International Journal, 41(3), 374-388. https://doi.org/10.1108/ER-04-2018-0100

Gaspar, T., Faia-Correia, M., Machado, M.C., Xavier, M., Guedes, F.B., Pais-Ribeiro, J., & Matos, M.G. (2022). Ecossistemas dos Ambientes de Trabalho Saudáveis (EATS): Instrumento de Avaliação dos Healthy Workplaces. Revista Psicologia, Saúde & Doenças, 23(1), 252-268.

Gaspar, T., Botelho-Guedes, F., Cerqueira, A., Baban, A., Rus, C., Matos, M. G. (2024) Burnout as a multidimensional phenomenon: how can workplaces be healthy environments? Journal of Public Health, 1-14. https://doi.org/10.1007/s10389-024-02223-0

Gaspar, T., Salado, V., Machado, M. D. C., Guedes, F. B., Correia, M. F., & Matos, M. G. (2023a). The Healthy Workplaces Ecosystems and Professionals’ Stress Management during the COVID-19 Pandemic. Sustainability, 15(14), 11432. https://doi.org/10.3390/su151411432

Gaspar, T., Telo, E., Rocha-Nogueira, J., & LABPATS (2023b). Manual de Boas Práticas: Promoção de Ambientes de Trabalho Saudáveis. Laboratório Português de Ambientes de Trabalho Saudáveis. ISBN: 978-989-98346-3-7

George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference 11.0 update (4ª ed.). Allyn & Bacon.

Harper, J. C., & Botero-Meneses, J. S. (2022). An online survey of UK women’s attitudes to having children, the age they want children and the effect of the COVID-19 pandemic. Human Reproduction, 37(11), 2611-2622. https://doi.org/10.1093/humrep/deac209

Janssen, D., & Carradini, S. (2021). Generation Z workplace communication habits and expectations. IEEE Transactions on Professional Communication, 64(2), 137-153. https://ieeexplore.ieee.org/abstract/document/9440009

Jung, H. S., & Yoon, H. H. (2021). Generational effects of workplace flexibility on work engagement, satisfaction, and commitment in South Korean deluxe hotels. Sustainability, 13(16), 9143. https://doi.org/10.3390/su13169143

Kim, J. H. (2021). The Relationship between Employee’s Work-Related Stress and Work Ability based on Qualitative Literature Analysis. The Journal of Industrial Distribution & Business, 12(7), 15-25. https://doi.org/10.13106/jidb.2021.vol12.no7.15

Krisdayanti, K., & Lianto, L. (2023). The Evolution of Work-Life Balance: The Workplace Hopes and Challenges for Generation Z. SEIKO: Journal of Management & Business, 6(2). https://doi.org/10.37531/sejaman.v6i2.5953

Kuokkanen, H., & Sun, W. (2020). Social desirability and cynicism biases in CSR surveys: An empirical study of hotels. Journal of Hospitality and Tourism Insights, 3(5), 567-588. https://doi.org/10.1108/JHTI-01-2020-0006

Lee, S. H., Chong, C. W., & Ojo, A. O. (2024). Influence of workplace flexibility on employee engagement among young generation. Cogent Business & Management, 11(1), 2309705. https://doi.org/10.1080/23311975.2024.2309705

Lestari, D., & Margaretha, M. (2021). Work life balance, job engagement and turnover intention: Experience from Y generation employees. Management Science Letters, 11(1), 157-170. https://m.growingscience.com/beta/msl/4183-work-life-balance-job-engagement-and-turnover-intention-experience-from-y-generation-employees.html

Lu, S., Wei, F., & Li, G. (2021). The evolution of the concept of stress and the framework of the stress system. Cell Stress, 5(6), 76. https://doi.org/10.15698%2Fcst2021.06.250

Machová, R., Zsigmond, T., Lazányi, K., & Krepszová, V. (2020). Gerações e inteligência emocional um estudo piloto. Acta Polytechnica Hungarica, 17 (5), 229-247. https://www.academia.edu/download/66218249/17._ACTA_Zsigmond.pdf

Mahmoud, A. B., Fuxman, L., Mohr, I., Reisel, W. D., & Grigoriou, N. (2021). “We aren’t your reincarnation!” workplace motivation across X, Y and Z generations. International Journal of Manpower, 42(1), 193-209. https://doi.org/10.1108/IJM-09-2019-0448

Marôco, J. (2021). Análise Estatística com o SPSS Statistics (8ª ed.). ReportNumber.

Martinez, M. C., & Fischer, F. M. (2019). Fatores psicossociais no trabalho hospitalar: situações vivenciadas para desgaste no trabalho e desequilíbrio entre esforço e recompensa. Revista Brasileira de Saúde Ocupacional. https://doi.org/10.1590/2317-6369000025918

Matos, M., Wainwright, T., Ribeiro, J. L. P., Leal., I., Gaspar, T., Correia, M. F., Costa, J., Calado, P., Delgado, A., Coelho, L., Machado, M. C., Santos, O., Behrens, T. & Ricou, M. (2020). O Futuro de Quase Tudo. Ordem dos Psicólogos Portugueses.

Miteva, S., Stoyanova, S., & Damyanova-Andreeva, M. (2024). Generational differences in preferences for coping with stress. Knowledge-International Journal, 65(1), 171-176. https://ikm.mk/ojs/index.php/kij/article/view/6911

Nanda, A., Soelton, M., Luiza, S., & Saratian, E. T. P. (2020). The effect of psychological work environment and work loads on turnover interest, work stress as an intervening variable. Atlantis Press. https://doi.org/10.2991/aebmr.k.200205.040

Oksa, R., Saari, T., Kaakinen, M., & Oksanen, A. (2021). The motivations for and well-being implications of social media use at work among millennials and members of former generations. International journal of environmental research and public health, 18(2), 803. https://doi.org/10.3390/ijerph18020803

Pasla, P., Asepta, U., Widyaningrum, S., Pramesti, M., & Wicaksono, S. (2021). The effect of work from home and work load on work-life balance of generation X and generation Y employees. Journal of Economics, Finance and Accounting Studies, 3(2), 220-224. https://doi.org/10.32996/jefas.2021.3.2.21

Patro, C. S., & Kumar, K. S. (2019). Effect of workplace stress management strategies on employees’ efficiency. International Journal of Scientific Development and Research, 4(5), 412-418.

Pereira, A. C. L., Souza, H. A., Lucca, S. R. D., & Iguti, A. M. (2020). Fatores de riscos psicossociais no trabalho: limitações para uma abordagem integral da saúde mental relacionada ao trabalho. Revista Brasileira de Saúde Ocupacional. https://doi.org/10.1590/2317-6369000035118

Rugulies, R. (2019). What is a psychosocial work environment?. Scandinavian journal of work, environment & health, 45(1), 1-6. https://doi.org/10.5271/sjweh.3792

Saba, T. (2021). Understanding generational differences in the workplace: Findings and conclusions. https://policycommons.net/artifacts/1934280/understanding-generational-differences-in-the-workplace/2686050/

Sakroni, S. (2024). The role of social support in managing stress among generation z in bandung. Journal of humanities, social sciences and business, 3(4), 1007-1016. https://doi.org/10.55047/jhssb.v3i4.1341

Sharma, D. (2023). To Identify Stress in the Services Sector. In Strategic Human Resource Management in the Hospitality Industry: A Digitalized Economic Paradigm (pp. 255-266). IGI Global.

Sinta, L. E., & Dwiyanti, E. (2023). Relationship between Marital Status and Mental Workload with Work Stress for Work From Home Workers. The Indonesian Journal of Occupational Safety and Health, 12(2), 185-193. https://doi.org/10.20473/ijosh.v12i2.2023.185-193

Spiess, T., Ploder, C., Bernsteiner, R., & Dilger, T. (2021). Techno-stress in the workplace: Triggers, outcomes, and coping strategies with a special focus on generational differences. International Journal of Web Engineering and Technology, 16(3), 217-234. https://doi.org/10.1504/IJWET.2021.119875

Standifer, R. L., & Lester, S. W. (2020). Actual versus perceived generational differences in the preferred working context: An empirical study. Journal of Intergenerational Relationships, 18(1), 48-70. https://doi.org/10.1080/15350770.2019.1618778

Stevanin, S., Voutilainen, A., Bressan, V., Vehviläinen-Julkunen, K., Rosolen, V., & Kvist, T. (2020). Nurses’ generational differences related to workplace and leadership in two European countries. Western Journal of Nursing Research, 42(1), 14-23. https://doi.org/10.1177/0193945919838604

Stobiecka, J., & Pangsy-Kania, S. (2021). Managing stress as a key element of the competition in the workplace based on the example of generations Y and Z. International Business Information Management Association.

Todorova, A. (2024). Examining emotional intelligence evolution with age: insights from Bulgarian digital entrepreneurs of different generations. IIMT Journal of Management. https://doi.org/10.1108/IIMTJM-12-2023-0075

Torre, G., Manai, M. V., Shaholli, D., Chiappetta, M., Cocchiara, R. A., & Casini, L. (2024). Are the size of the organizational units and the type of activities of an information technology company associated to the level of work-related stress indicators? Results of an observational study in Italy. Journal of Public Health, 1–11. https://doi.org/10.1007/s10389-024-02318-8

Varianou-Mikellidou, C., Boustras, G., Nicolaidou, O., Dimopoulos, C., Anyfantis, I., & Messios, P. (2020). Work-related factors and individual characteristics affecting work ability of different age groups. Safety Science, 128, 104755.

Younas, M. & Bari, M. W. (2020). The relationship between talent management practices and retention of generation ‘Y’ employees: mediating role of competency development. Economic Research-Ekonomska Istraživanja, 33(1), 1330-1353.