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Purpose

Grounded in the job demands-resources (JD-R) theory, this study seeks to uncover the factors influencing workplace presenteeism and explore its impact on psychological withdrawal, focusing on the moderating role of job tension in this relationship.

Design/methodology/approach

A quantitative research design was adopted, utilising a survey to collect data from 256 employees across various service sectors in Oman, employing partial least squares structural equation modelling.

Findings

The analysis revealed that presenteeism is significantly influenced by time pressure and abusive supervision, whereas job insecurity did not show such an effect. Furthermore, a strong relationship was identified between presenteeism and psychological withdrawal, with job tension significantly moderating this connection. Notably, presenteeism was found to mediate the relationship between its predictors, excluding job insecurity and psychological withdrawal.

Originality/value

Given the importance of human capital, engagement and presenteeism at work, findings offer valuable insights for both academia and service industry managers to guide their management decisions and strategies.

Presenteeism has received much attention in various fields due to its impact on organisations and individuals (Homrich et al., 2020; Islam et al., 2024). Presenteeism occurs when employees continue to work while being sick, resulting in lower productivity and performance (Van Waeyenberg, 2024). Presenteeism was first presented as a personal or health-related issue, but it is now widely acknowledged as a strategic organisational issue, especially in high-demand service sectors like healthcare, where staff presence is essential, but unchecked attendance while sick can endanger customer satisfaction and employee well-being (Marciniak-Nuqui et al., 2024; Van Waeyenberg, 2024). For instance, employees who engage in presenteeism may experience lower job satisfaction, higher stress levels, and poorer physical and mental health (Deery et al., 2014). Working while sick can also slow healing, prolong illness, and raise the risk of infectious disease transmission to coworkers (Karanika-Murray et al., 2015).

Moreover, presenteeism may negatively affect overall productivity, performance, and job quality in organisations (Islam et al., 2024). Workers may experience decreased creativity, cognitive function, and lack of focus, which could lead to subpar results (Biron et al., 2022). Employees who push themselves to work while sick may experience more serious health issues and take longer to recover (Bergström et al., 2009; Hung et al., 2024; Islam et al., 2024).

According to Marciniak-Nuqui et al. (2024), presenteeism may endanger patient workers, particularly those working in medical facilities. In other words, healthcare employees who work while sick may inadvertently expose their patients to infectious diseases, putting their own health and well-being at risk. This problem can occur in hospitals and long-term care facilities, where vulnerable individuals are more likely to get infections (Biron et al., 2022; Marciniak-Nuqui et al., 2024).

Given the importance of presenteeism, healthcare organisations are advised to address such issues to prevent disease spread and ensure patient safety (Homrich et al., 2020; Hung et al., 2024). However, scholars have noted that the antecedents and outcomes of presenteeism remain scarce in the current literature (Patel et al., 2023; Yıldız et al., 2015). A study conducted within the Turkish healthcare system involving 168 employees found that antecedents such as working-time mismatch and efficiency demand are associated with presenteeism. Findings revealed that aligning desired and actual weekly working hours, as well as reducing efficiency demands, decreases presenteeism (Yıldız et al., 2015).

Prior studies on presenteeism have yielded conflicting findings, leaving the concept unclear and requiring further investigation (Marciniak-Nuqui et al., 2024; Ruhle et al., 2020). For instance, presenteeism shows a strong negative correlation with both personal well-being and professional performance, according to longitudinal studies that lasted over a year (Skagen and Collins, 2016). Yet, presenteeism has been positively correlated with both mental health (Yoo et al., 2022) and job performance (Lu et al., 2013) in shorter-term research. Using a sample of 361 respondents, Chou and Mach (2021) investigated the impact of presenteeism on work-related outcomes in Taiwan, including work engagement, job performance, and emotional weariness. They found that presenteeism is positively correlated with emotional exhaustion but negatively correlated with performance and engagement.

To examine the impact of presenteeism on employees' performance evaluation, Wang et al. (2023) reported positive results when adopting the social cognitive framework and trait activation theory in two experimental scenario studies. The Job Demands-Resources (JD-R) theory posits that a mismatch between an employee's abilities and job expectations, driven by high job demands and inadequate resources, can result in higher levels of presenteeism (McGregor et al., 2016). However, several factors, such as a high workload, constrained schedules, project deadlines, or outside commitments, might lead to time pressure (Chen et al., 2022). Furthermore, when employees feel their jobs are insecure and fear the consequences of missing work, they might be more likely to engage in presenteeism to keep their jobs (Kim et al., 2020). Time constraints and job uncertainty are therefore regarded as antecedents of presenteeism. Still, the degree to which time pressure and job insecurity affect presenteeism may be influenced by abusive supervision (Mao et al., 2019).

According to Lee et al. (2021), employees who experience abusive supervision may feel pressured to go to work even when they are sick due to their fear of the supervisor's response or repercussions. This could lead to more mistakes, lower productivity, and a higher risk of infectious diseases spreading at the workplace (Dhali et al., 2023). In this instance, we believe that presenteeism might result in psychological withdrawal, particularly when employees who are physically present but mentally absent produce less, make inappropriate decisions, and even more mistakes (Silva-Costa et al., 2020). The association between presenteeism and psychological withdrawal may be getting stronger or weaker under the influence of work-related tension.

Indeed, presenteeism is an issue that may lead to poor decision-making, less creativity, poorer cognitive functioning, an increased risk of virus transmission, and burnout (Deery et al., 2014). However, the causes and effects of presenteeism remain theoretically incoherent and empirically inconsistent despite a growing volume of research (Ruhle et al., 2020), calling for a more comprehensive paradigm. Scholars across various fields, legislators, and professionals are increasingly interested in developing a better understanding of the causes and consequences of presenteeism, given its complex effects on both individual well-being and organisational efficiency (Patel et al., 2023).

To fill this gap, this study employs the JD-R theory to investigate the presenteeism antecedents and outcomes. The association between antecedents like time pressure, job instability, and abusive supervision, and psychological withdrawal or detachment (i.e. the mental disengagement while physically present) is thought to be mediated by presenteeism (Silva-Costa et al., 2020).

Building on previous research examining human resource management (HRM) stress (Bhaskar and Alam, 2023), our study includes a perspective on transformative workplace models and digital innovation (Bhaskar and Reeta, 2025). These findings highlight the importance of proactive human resource (HR) strategies that reduce presenteeism by identifying hidden pressures and enhancing employee experience, especially in critical, high-touch service sectors. This study bridges theory and practice by connecting presenteeism with broader organisational efficiency models and future-oriented HR initiatives. Factors such as time pressure, job insecurity, and abusive supervisors contribute to presenteeism (Silva-Costa et al., 2020). Our research also explores how job tension influences the relationship between presenteeism and psychological withdrawal. Moreover, we investigate the role of presenteeism as a mediator between psychological withdrawal and its potential causes, including time pressure, job insecurity, and abusive supervision.

Accordingly, this study makes three major contributions. First, it expands on the JD-R theory by showing how abusive supervision, often seen as a leadership problem, functions as a persistent job demand that indirectly leads to withdrawal through presenteeism. Second, it empirically examines the moderating role of job tension, offering detailed insights into the early signs and development of presenteeism. Third, it addresses practical HRM strategies and operational challenges by providing managerial and policy recommendations to reduce lost productivity and safeguard employee well-being. In doing so, this study not only advances theorising on presenteeism but also highlights a key practice-oriented issue, namely, how service industries can identify hidden drivers of employee withdrawal and shift the focus from attendance quantity to quality of work.

The study is organised as follows: Section 2 outlines the current literature and hypotheses development. Section 3 explains the methods, followed by sections 3 and 4, which discuss the study results and findings. Finally, the theoretical and practical implications, limitations, and suggestions for future research avenues are highlighted at the end.

The JD-R model is an employment-based stress model that posits that strain arises when job demands exceed the resources available to cope with them (Demerouti et al., 2001). Job demands are aspects of the job that require sustained physical or psychological effort and are associated with physiological or psychological costs, such as high workload or emotional demands (Tummers and Bakker, 2021). Job resources, in contrast, are aspects of the job that help employees manage demands, achieve their work goals, and promote personal or professional growth, including autonomy, social support, constructive feedback, and opportunities for development (Arthur et al., 2025; Soliman et al., 2024a). In line with this framework, in our model, time pressure, job insecurity, abusive supervision, and job tension are conceptualised as job demands, as they require sustained effort and are likely to increase stress. Psychological withdrawal and presenteeism are not treated as job demands or resources but as behavioural strain reactions that may emerge when employees experience high demands and insufficient resources. Psychological withdrawal reflects a coping mechanism by which employees mentally disengage from their work role in an attempt to conserve remaining resources, whereas presenteeism reflects continued attendance at work despite reduced capacity, typically leading to negative consequences for both the employee and the organisation. Thus, within the JD-R model, job demands (time pressure, job insecurity, abusive supervision, and job tension) are expected to trigger strain, which can manifest behaviourally as psychological withdrawal and presenteeism (Bakker and Demerouti, 2007; McGregor et al., 2016).

Time pressure is the psychological tension that an individual experiences when they believe they have insufficient time to complete a task or achieve a desired outcome. It is the feeling of urgency or the restricted time frame that exists to complete a task or satisfy a deadline (Sussman and Sekuler, 2022). Time pressure can result from a variety of sources, including high responsibilities, tight timetables, project deadlines, or external factors (Chen et al., 2022). The consequences of time pressure may vary depending on the circumstances and a person's ability to manage it. Inadequate judgement or errors, performing problems, lower productivity, stress, and poor health are among the most prevalent consequences of time pressure (Alqahtani et al., 2018).

Presenteeism refers to the situation in which employees are physically present at work but do not fully engage or produce due to health problems, stress, or personal issues (Mohammadi et al., 2021). This can result in lower productivity and higher expenses for companies (Widera et al., 2010). There are multiple elements to presenteeism, including health-related presenteeism, which occurs when workers stay at work regardless of being ill due to mental or physical problems; psychological presenteeism, which occurs when employees are psychologically detached due to stress or exhaustion; workplace customs and culture, which force employees to go to work irrespective of their good health; and economic variables, including job uncertainty, that encourage workers to keep their jobs while ill to prevent financial harm (Johns, 2010). Organisations that are interested in improving worker efficiency and happiness by addressing the underlying causes of presenteeism must comprehend these dimensions.

Presenteeism in work environments can be substantially influenced by time pressure, both directly and indirectly, through a variety of mechanisms (Dietz and Scheel, 2017). The immediate consequences include the induction of a sense of urgency and the obligation to be physically present at work, even when individuals do not feel good. Regardless of their health status, employees may feel obligated to attend work to meet deadlines or workplace requirements (Widera et al., 2010). Employees' views and experiences are considered indirect consequences. Indeed, when individuals experience time pressure, they may feel overwhelmed, stressed, or unable to allocate sufficient time for self-care and recovery. This can exacerbate health issues and increase the likelihood of presenteeism (Golden, 2012). Moreover, time pressure can contribute to the accumulation of work, leading to higher levels of stress and the perception that attending work while ill is necessary (Miraglia and Johns, 2015).

Prior research has explored the link between time pressure and presenteeism, with Dietz and Scheel (2017) specifically examining how time constraints influence presenteeism among PhD students and postdocs in German scientific institutes, revealing that time pressure partially mediates the positive effect of supervisorial pressure on presenteeism. Also, Jia et al. (2022) evaluated the direct effects of work stress, health status, and presenteeism on task performance among Chinese medical staff during the COVID-19 pandemic. They observed that work stress, which includes time pressure, was positively correlated with presenteeism. Moreover, Ho et al. (2022) found that time pressure leads sickness presenteeism among employees working in Malaysia. Moreover, Nordenmark et al. (2019) examined sickness presenteeism among self-employed and organisationally employed individuals in northwestern Europe, finding that higher time demands significantly increase the likelihood of working while ill, even after accounting for background variables. In today's fast-paced work environments, increasing time pressure has been consistently linked to a higher incidence of presenteeism. A piece of research conducted on disaster responders, deployed after Japan's Noto Peninsula earthquake in 2024, demonstrated that more work days led directly to increased presenteeism, with fatigue exerting a modest buffering effect (Khaing et al., 2025). Based on these results, the first hypothesis of this study is:

H1.

Time pressure has a positive and significant relationship with presenteeism.

Job insecurity refers to the perceived or anticipated threat of losing one's job or the instability and uncertainty surrounding employment (Soliman et al., 2023b). It is distinguished by a lack of assurance regarding the ongoing success and security of a job (Chirumbolo et al., 2022). Job insecurity can result from a variety of factors, such as economic turmoil, advances in technology, organisational restructuring, and sector changes (Ghani et al., 2022). The consequences of job insecurity can be detrimental to both workers and their employers (Shoss et al., 2022). It results in a variety of negative effects, such as a negative work environment, decreased productivity, increased tension, lower mood, reduced work satisfaction, worsened dedication to the company, incompatible job behaviours, and worsened work performance (Soliman et al., 2021, 2023b). Fostering employment insecurity can be detrimental to both workers and their employers (Sverke et al., 2019). Presenteeism may be more prevalent among individuals who perceive job insecurity as a means of securing their employment or who are concerned about the adverse repercussions of being absent (Kim et al., 2020).

The correlation between job insecurity and presenteeism has been explored by prior work (Li, 2023). In a study by Kim et al. (2020), that included 19,720 full-time waged workers in South Korea, it was discovered that presenteeism was correlated with perceived job insecurity, but absenteeism was not. The research showed that employees who felt uncomfortable with their jobs were more likely to engage in presenteeism for at least 2 days per year. Schmidt and Pförtner (2020) analysed data from Germany's 2012 BIBB/BAuA Employment Survey and found that job insecurity increased the risk of presenteeism, but this effect disappeared in companies with health promotion initiatives, highlighting their protective role. A study conducted in China by Zhang et al. (2020) with a sample of 330 nurses found that job insecurity was positively associated with presenteeism. A 2025 cross-sectional study conducted among employees at an Indonesian company found that job insecurity was significantly linked to presenteeism; 77.8% of respondents reported going to work while sick, with job insecurity emerging as a key predictor alongside gender differences (Salsabil, 2025). Furthermore, a 2024 mixed-methods investigation within the education sector revealed that avoidance-motives presenteeism (attending work to avoid negative job outcomes) served as a mediating mechanism in the pathway between job insecurity and employees' sustained employability (Humayun et al., 2024). Therefore, the second hypothesis is formulated as follows:

H2.

Job insecurity is positively and significantly associated with presenteeism.

An abusive supervisor is a manager or leader who consistently engages in hostile, demeaning, or harmful behaviour toward subordinates. This type of supervisor exhibits destructive leadership behaviours that negatively impact the well-being, performance, and attitudes of their direct reports, as well as the organisation's overall functioning (Tran et al., 2014). The outcomes of abusive supervision can be severe and wide-ranging. Employees who experience abusive supervision may exhibit workplace deviance, such as engaging in counterproductive work behaviours or acts of aggression (Gallegos et al., 2022). Also, they are more susceptible to mental exhaustion, diminished job satisfaction and commitment to the organisation, and higher leave intentions (Bhattacharjee and Sarkar, 2022). Furthermore, abusive supervision has been associated with adverse mental and physical consequences for employees, such as tension, depressive disorders, anxiety, and medical conditions (Gallegos et al., 2022).

Presenteeism is one instance of oppressive supervision. Employees may be forced to come to work despite their poor health due to the worry about negative consequences or punishment from their supervisor when they are subjected to abusive supervision. This can increase the likelihood of disease spread in the workplace, lead to greater errors, and lower productivity (Lee et al., 2021). Lee et al. (2021) examined the correlation between presenteeism and the behaviours of the direct supervisor among wage labourers in South Korea. They discovered that the conduct of a direct supervisor can have a substantial impact on employee presenteeism. A 2024 study of full-time employees in Egyptian five-star hotels found that abusive leadership notably increased presenteeism, which subsequently mediated the negative effect of such leadership on job engagement through perceived organisational politics (Salama et al., 2025). The third hypothesis is developed in accordance with these inputs, as follows:

H3.

An abusive supervisor has a positive and significant relationship with presenteeism.

Presenteeism refers to employees being physically at the workplace but lacking full engagement or productivity due to factors such as illness, fatigue, or personal issues, often leading to psychological withdrawal (Magalhães et al., 2022). Psychological withdrawal is characterized by a psychological distancing or separation from job duties and tasks. It may encompass emotional exhaustion, a lack of inspiration, diminished satisfaction with work, and feelings of disengagement. Employees may experience reduced output, weakened decision-making, and an increase in mistakes or mishaps when they are physically present but psychologically withdraw (Silva-Costa et al., 2020).

The relationship between psychological withdrawal and presenteeism has been emphasised in previous research. For instance, a study conducted by Chou and Mach (2021) on Chinese employees in Taiwan discovered that presenteeism was associated with psychological withdrawal. This suggests that employees who participated in presenteeism were more likely to suffer from psychological withdrawal from work. In addition, presenteeism has been linked to prevalent mental disorders among nurses at a public hospital in Brazil, where it serves as a mediator between the psychosocial aspects of employment and psychological outcomes (Silva-Costa et al., 2020). These findings indicate that having a history of presenteeism can exacerbate psychological distress and psychological problems in employees. Furthermore, a study conducted by Cocker et al. (2013) in Australian small-to-medium enterprise owners/managers discovered that depression-related presenteeism can result in decreased productivity and psychological distress. The fourth hypothesis is developed in accordance with the preceding conversation, as follows:

H4.

Presenteeism has a positive and significant relationship with psychological withdrawal

The psychological and emotional distress that individuals encounter in their work environment is referred to as job tension. It is defined by the experience of tension, pressure, and conflict resulting from a variety of work-related factors. Predisposition variables are the underlying conditions or circumstances that increase the likelihood of individuals experiencing job tension. These factors may include individual features, such as personality types and coping styles, as well as organisational variables, such as high job demands, a lack of control, interpersonal difficulties, and insufficient systems of support (Bhui et al., 2016). Employees may experience greater stress and strain due to presenteeism, which can contribute to job tension by compelling them to work despite their poor health (Laranjeira et al., 2022). Kim et al. (2019) investigated the link between job stress and presenteeism experience among Korean labourers. Their results indicated that presenteeism was significantly correlated with job-related stress in the general population.

Psychological withdrawal can also be influenced by job tension, and people may experience exhaustion, fatigue, and an absence of emotional fulfilment (Taris et al., 2001). A high level of job stress can lead to emotional and mental fatigue, increasing the likelihood that employees will withdraw from their job responsibilities. In the same vein, occurrences of psychological withdrawal are predicted by elevated levels of stress, which correspond to a lack of power and autonomy in the workplace (Jamil et al., 2023). Furthermore, work stress reduces job satisfaction, which can result in psychological withdrawal (Nazir et al., 2022). A study discovered that job stress has a negative correlation with job satisfaction among university staff. This suggests that increased stress levels reduce job satisfaction, thereby fostering withdrawal patterns (Wang et al., 2020). Consequently, the fifth hypothesis is:

H5.

Job tension positively moderates the link between presenteeism and psychological withdrawal.

The mediating function of presenteeism has been further explored in numerous studies, with a particular emphasis on its influence on company performance, staff well-being, and productivity. Job satisfaction and presenteeism were identified as mediating factors in a study examining the linkage between job stress and attrition tendency of primary healthcare workers. Presenteeism is found to mediate the impact of job stress on turnover intention, indicating that employees experiencing elevated levels of stress are more likely to engage in presenteeism, which in turn affects their intention to quit (Ning et al., 2023). Presenteeism was used as a mediating variable in the relationship between job demands (such as work overload, understaffing, and attendance enforcement) and subsequent absenteeism (Deery et al., 2014). Zhang et al. (2020) conducted a study in China that discovered that presenteeism partially mediated the association between emotional exhaustion and job insecurity among nurses. These studies collectively emphasise the intricate function of presenteeism as a mediator. Addressing the factors that drive presenteeism and fostering supportive work environments can help mitigate its negative effects on employee health and productivity. As literature lacked investigation of the mediating role of presenteeism, we developed the following hypotheses:

H6.

Presenteeism mediates the link between time pressure and psychological withdrawal.

H7.

Presenteeism mediates the link between job insecurity and psychological withdrawal.

H8.

Presenteeism mediates the link between abusive supervisors and psychological withdrawal.

Based on the previous literature, Figure 1 below presents the research model.

Figure 1
A conceptual model linking time pressure, job insecurity, and abusive supervision to presenteeism and withdrawal.The conceptual model shows a dashed rectangular box on the left containing three vertically stacked rectangles labeled “Time pressure”, “Job insecurity”, and “Abusive supervisor”. Each of these three rectangles has a rightward-pointing arrow directed towards a central rectangle labeled “Presenteeism”. The arrow from “Time pressure” is labeled “H 1”, the arrow from “Job insecurity” is labeled “H 2”, and the arrow from “Abusive supervisor” is labeled “H 3”. From the central rectangle “Presenteeism”, a solid rightward arrow labeled “H 4” leads to a rectangle labeled “Psychological withdrawal” on the right side of the diagram. Above this main pathway, a rectangle labeled “Job tension” is positioned at the top. A downward-pointing arrow labeled “H 5” extends from “Job tension” to the arrow connecting “Presenteeism” and “Psychological withdrawal”, indicating a moderating effect. A dashed horizontal arrow labeled “H 6, H 8” extends from the left dashed box towards “Psychological withdrawal”. In addition, a vertical dashed line extends downward from “Presenteeism” to meet the dashed arrow labeled “H 6, H 8”.

The conceptual model. Source: The authors

Figure 1
A conceptual model linking time pressure, job insecurity, and abusive supervision to presenteeism and withdrawal.The conceptual model shows a dashed rectangular box on the left containing three vertically stacked rectangles labeled “Time pressure”, “Job insecurity”, and “Abusive supervisor”. Each of these three rectangles has a rightward-pointing arrow directed towards a central rectangle labeled “Presenteeism”. The arrow from “Time pressure” is labeled “H 1”, the arrow from “Job insecurity” is labeled “H 2”, and the arrow from “Abusive supervisor” is labeled “H 3”. From the central rectangle “Presenteeism”, a solid rightward arrow labeled “H 4” leads to a rectangle labeled “Psychological withdrawal” on the right side of the diagram. Above this main pathway, a rectangle labeled “Job tension” is positioned at the top. A downward-pointing arrow labeled “H 5” extends from “Job tension” to the arrow connecting “Presenteeism” and “Psychological withdrawal”, indicating a moderating effect. A dashed horizontal arrow labeled “H 6, H 8” extends from the left dashed box towards “Psychological withdrawal”. In addition, a vertical dashed line extends downward from “Presenteeism” to meet the dashed arrow labeled “H 6, H 8”.

The conceptual model. Source: The authors

Close modal

Following a quantitative approach, the conceptual model comprises six latent variables, each measured reflectively. Measurement scales for these variables were selected from relevant prior studies and applied within the service industry context. Time pressure is assessed using four items from Nguyen-Phuoc et al. (2022). Job insecurity is assessed using four items taken from Soliman et al. (2021). Abusive supervision is analysed by adapting six items from Harvey et al. (2014). Presenteeism is measured employing six items adapted from Koopman et al. (2002). Job tension is assessed with seven items derived from Soliman et al. (2023a). Psychological withdrawal is evaluated using eight items (Lehman and Simpson, 1992). All items were measured using a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).

This study primarily targets employees working in various sectors of Oman's service industry, specifically banking, logistics, healthcare, and tourism and hospitality. The selection of these sectors is based on two main reasons: the substantial number of employees they encompass and the distinctive characteristics of their work environments. The current research utilised a combination of non-probability sampling techniques due to the large number of participants. Specifically, this study employed convenience sampling by distributing an online survey to potential respondents in the targeted sectors via social networking platforms like WhatsApp. Besides, self-selection sampling was implemented by sending the survey link directly to participants. Furthermore, snowball sampling was utilised by asking some participants to share the survey link with their contacts.

The data collection process involved administering an online survey structured into multiple key sections. Initially, a cover page was presented, followed by a preliminary section featuring a screening question to secure respondents' informed consent. Subsequently, a set of 35 items was included to assess six underlying constructs. This was followed by a demographic section gathering information on participants' characteristics, including age, gender, marital status, educational background, and professional experience. To ensure linguistic accessibility for native Arabic speakers, the survey was originally crafted in English and later translated into Arabic using a back-translation method.

Between April 21, 2024, and June 13, 2024, 256 responses were gathered and considered valid for further analysis. Table 1 presents the demographic characteristics of the sample. In terms of age, around 83% of participants were between 20 and 40 years old. 162 were female, and 94 were male, with 52% married and 35% single. Concerning education, 51% held a bachelor's degree, 28% possessed a diploma degree, and 12% had a master's degree. Regarding work experience, 29% had 2–5 years, 22% had 6–10 years, and 27% had more than 10 years. Around 47% of respondents are employed in the health sector, 23% in the banking sector, 23% in the logistics sector, and 7% in the tourism and hospitality sector.

Table 1

Sample profile

FeatureCategoryFrequencyPercentage
Age20–30 years10842.188%
31–40 years10440.625%
41–50 years3714.453%
More than 50 years72.734%
GenderMale9436.719%
Female16263.281%
Marital statusSingle8934.766%
Married13351.953%
Divorced176.641%
Widowed124.688%
Others51.953%
EducationDiploma degree7127.734%
Bachelor's degree13151.172%
Master's degree3112.109%
Doctorate degree145.469%
Others93.516%
Work experienceLess than 2 years5722.266%
2–5 years7428.906%
6–10 years5621.875%
More than 10 years6926.953%
SectorHealth sector12046.875%
Banking sector5923.047%
Logistics sector5822.656%
Tourism and hospitality sector197.422%
Total 256100%
Source(s): The authors

In the present paper, WarpPLS 8 (Kock, 2022) was employed to conduct the PLS-SEM analytical technique for data analysis and hypothesis testing. PLS-SEM was selected for several reasons. Firstly, it is well-suited for empirical studies that involve developing and examining structural frameworks comprising multiple-indicator variables. Secondly, PLS-SEM is appropriate for assessing complex models that include both direct effects and indirect effects (such as moderation and mediation analyses) among the variables under study. Thirdly, this technique is solid for either developing or expanding theories (Manley et al., 2021). Fourthly, PLS-SEM has been widely utilised in previous studies across various contexts, particularly within different sectors related to the service industry (Anasori et al., 2022, 2023; Durrah et al., 2025; Elzek et al., 2024; Selmi et al., 2025; Soliman et al., 2024b). The PLS-SEM approach typically involves two main phases: evaluating the measurement model and assessing the structural model (Kock, 2022; Manley et al., 2021).

This study employed the full collinearity test to evaluate the presence of common method bias/variance (CMV). In accordance with the recommendations of Kock (2022), a variance inflation factor (VIF) of 3.3 or lower signifies that the model is not substantially influenced by CMV. As presented in Table 2 reported below, the computed VIF values for all variables ranged between 1.621 and 3.080, indicating that CMV did not pose a significant concern in this research.

Table 2

Reliability, convergent validity, and CMV

Variables/itemsItem loadingsp valueComposite reliabilityCronbach's alphaAVEFull collinearity VIF
Time pressure 0.8950.8430.6801.621
TP1(0.811)<0.001    
TP2(0.869)<0.001    
TP3(0.846)<0.001    
TP4(0.769)<0.001    
Job insecurity 0.8680.7720.6871.844
JI1(0.806)<0.001    
JI2(0.821)<0.001    
JI3R    
JI4(0.859)<0.001    
Abusive supervision 0.9280.9060.6822.014
AS1(0.801)<0.001    
AS2(0.764)<0.001    
AS3(0.829)<0.001    
AS4(0.808)<0.001    
AS5(0.879)<0.001    
AS6(0.868)<0.001    
Presenteeism 0.9110.8820.6302.261
PR1(0.773)<0.001    
PR2(0.796)<0.001    
PR3(0.804)<0.001    
PR4(0.756)<0.001    
PR5(0.822)<0.001    
PR6(0.809)<0.001    
Job tension 0.9360.9200.6753.080
JT1(0.822)<0.001    
JT2(0.832)<0.001    
JT3(0.804)<0.001    
JT4(0.828)<0.001    
JT5(0.857)<0.001    
JT6(0.808)<0.001    
JT7(0.797)<0.001    
Psychological withdrawal 0.9200.8960.6582.696
PW1R    
PW2R    
PW3(0.791)<0.001    
PW4(0.799)<0.001    
PW5(0.855)<0.001    
PW6(0.826)<0.001    
PW7(0.775)<0.001    
PW8(0.821)<0.001    

Note(s): R = removed item

Source(s): The authors

Assessing the measurement model requires verifying the construct reliability and validity through the following steps (Hair et al., 2020). Firstly, factor loadings must surpass 0.70. Consequently, three items were eliminated: one relating to job insecurity (JI3) and two relating to psychological withdrawal (PW1 and PW2), as their loadings were below 0.70, as reported in Table 2 below. Subsequently, the analysis was repeated, verifying that all remaining loadings exceed 0.70 and are statistically significant, as indicated by p-values below 0.05. Thus, the reliability of the indicators has been assured. Secondly, internal consistency reliability was established as the values of composite reliability (CR) and Cronbach's alpha for all latent variables surpassed the recommended threshold of 0.70. Thirdly, the AVE values exceeded 0.50, confirming the establishment of convergent validity, as reported in the following Table 2.

Fourthly, to ensure discriminant validity, this study utilised the widely recognised methods of Fornell and Larcker (1981) and the HTMT ratio by Henseler et al. (2015). Fornell and Larcker's (1981) approach verifies that the square root of each variable's AVE is greater than its correlations with other variables. Furthermore, the conservative HTMT.85 threshold was met, with all HTMT1 and HTMT2 ratios for latent variables below 0.85 (Table 3). The HTMT2 was used as it yields correlation estimates between latent variables that are less biased than those from HTMT, especially when the indicator loadings vary widely (Roemer et al., 2021). Therefore, discriminant validity was ensured, as shown in Table 3.

Table 3

Discriminant validity

VariablesTPJIASPRJTPW
Fornell and Larcker
TP0.825     
JI0.4770.829    
AS0.2990.5540.826   
PR0.5020.4060.5000.794  
JT0.5180.4910.5620.7200.822 
PW0.3750.5640.6530.5660.7120.811
Note(s): Italic values are the SQRT of AVEs
HTMT ratios
TP      
JI0.595     
AS0.3490.663    
PR0.5830.4930.562   
JT0.5890.5840.6180.800  
PW0.4350.6770.7250.6400.786 
HTMT2 ratios
TP      
JI0.581     
AS0.3270.661    
PR0.5840.4870.555   
JT0.5840.5740.6110.799  
PW0.4240.6720.7210.6300.782 

Note(s): HTMT ratios (good if < 0.90, best if < 0.85)

Source(s): The authors

The first step in assessing the structural model is to check for collinearity using the inner VIF (Hair et al., 2020). As shown in Table 4 below, results confirm the absence of multicollinearity since each variable's VIF is below 3.3 (Kock, 2022). The next phase involves evaluating the size and statistical significance of the path coefficients (β), which leads to testing the research hypotheses. The findings presented in Figure 2 and Table 4 reported below indicate that presenteeism is significantly and positively influenced by time pressure (β = 0.383, p < 0.001) and abusive supervision (β = 0.377, p < 0.001), thereby supporting H1 and H3. Conversely, there is no significant relationship between job insecurity and presenteeism (β = 0.014, p = 0.410), thereby rejecting H2. Moreover, presenteeism has a significant and positive link with psychological withdrawal (β = 0.538, p < 0.001), confirming H4.

Table 4

Hypotheses testing

HypothesesPath coefficient (β)p valueInner VIFSupported?Effect size (f2)
Direct effects
H1: TP → PR0.383<0.0011.297Yes0.192
H2: JI → PR0.0140.4101.705No0.006
H3: AS → PR0.377<0.0011.447Yes0.188
H4: PR → PW0.538<0.0011.030Yes0.305
Indirect effect (moderation)
H5: PR*JT → PW0.164<0.051.030Yes0.042
Indirect effect (mediation)
H6: TP → PR → PW0.206<0.001Yes0.077
H7: JI → PR → PW0.0080.431No0.004
H8: AS → PR → PW0.203<0.001Yes0.133
R2: PR = 0.386; PW = 0.347
Source(s): The authors
Figure 2
A structural model shows T P, J I, A S predicting P R, with P R predicting P W and J T.The structural model begins on the left with three oval shapes labeled “T P (R) 4 i”, “J I (R) 3 i”, and “A S (R) 6 i”. From “T P (R) 4 i”, a diagonal directional arrow proceeds toward the central oval “P R (R) 6 i”, annotated with “beta equals 0.38 (P less than 0.01)”. From “J I (R) 3 i”, a horizontal arrow also points to “P R (R) 6 i”, labeled “beta equals 0.01 (P equals 0.41)”. From “A S (R) 6 i”, another diagonal arrow leads upward to “P R (R) 6 i”, marked with “beta equals 0.38 (P less than 0.01)”. Beneath the central oval “P R (R) 6 i”, the value “R-squared equals 0.39” is shown. From “P R (R) 6 i”, a rightward directional arrow extends to the oval “P W (R) 6 i”, labeled “beta equals 0.54 (P less than 0.01)”, and beneath “P W (R) 6 i” the value “R-squared equals 0.35” is indicated. Above this main path, an oval labeled “J T (R) 7 i” is positioned at the top, with a vertical dotted arrow descending toward the arrow connecting “P R (R) 6 i” and “P W (R) 6 i”, annotated with “beta equals negative 0.16 (P less than 0.01)”.

The structural model. Source: The authors

Figure 2
A structural model shows T P, J I, A S predicting P R, with P R predicting P W and J T.The structural model begins on the left with three oval shapes labeled “T P (R) 4 i”, “J I (R) 3 i”, and “A S (R) 6 i”. From “T P (R) 4 i”, a diagonal directional arrow proceeds toward the central oval “P R (R) 6 i”, annotated with “beta equals 0.38 (P less than 0.01)”. From “J I (R) 3 i”, a horizontal arrow also points to “P R (R) 6 i”, labeled “beta equals 0.01 (P equals 0.41)”. From “A S (R) 6 i”, another diagonal arrow leads upward to “P R (R) 6 i”, marked with “beta equals 0.38 (P less than 0.01)”. Beneath the central oval “P R (R) 6 i”, the value “R-squared equals 0.39” is shown. From “P R (R) 6 i”, a rightward directional arrow extends to the oval “P W (R) 6 i”, labeled “beta equals 0.54 (P less than 0.01)”, and beneath “P W (R) 6 i” the value “R-squared equals 0.35” is indicated. Above this main path, an oval labeled “J T (R) 7 i” is positioned at the top, with a vertical dotted arrow descending toward the arrow connecting “P R (R) 6 i” and “P W (R) 6 i”, annotated with “beta equals negative 0.16 (P less than 0.01)”.

The structural model. Source: The authors

Close modal

Further, it is found that job tension (JT) significantly and positively moderates the relationship between presenteeism (PR) and psychological withdrawal (PW) (β = 0.164, p < 0.05). Following Kock's (2022) approach, Figure 3 below displays the low-high values with data points, generated by WarpPLS 8, illustrating JT as a moderating variable. As depicted in Figure 3, the direct effect between PR and PW is stronger at high levels of JT compared to low levels. These results support H5.

Figure 3
Two scatter plots show P R, P W relationship, with a stronger positive trend under high job tension.The scatter plots are titled “(Low J T)” on the left and “(High J T)” on the right. In both plots, the horizontal axis is labeled P R and the vertical axis is labeled P W. In the Low J T plot, the horizontal axis shows P R values at negative 1.68, negative 1.03, negative 0.38, 0.26, 0.91, and 1.55. The vertical axis shows P W values at negative 1.25, negative 0.78, negative 0.30, 0.18, 0.66, and 1.14. Multiple circular data points are scattered across the graph, with a lightly sloped fitted line. In the Low J T plot, the fitted line starts near the lower left of the graph at approximately P R equals negative 1.68 and P W equals about negative 0.72, and ends near the upper right at approximately P R equals 1.55 and P W equals about 0.31. Scattered circular data points appear around the line, including points near P R equals negative 1.03 with P W around negative 0.80, near P R equals negative 0.38 with P W around negative 0.30, near P R equals 0.26 with P W around 0.20, near P R equals 0.91 with P W around 0.65, and near P R equals 1.55 with P W around 1.10. In the High J T plot, the horizontal axis shows P R values at negative 1.50, negative 0.76, negative 0.02, 0.72, 1.46, and 2.21. The vertical axis shows P W values at negative 1.25, negative 0.49, 0.28, 1.05, 1.82, and 2.58. The circular data points are more concentrated along an upward-sloping fitted line. The fitted line begins near the lower left at approximately P R equals negative 1.50 and P W equals about negative 0.42, and extends to the upper right ending near P R equals 2.21 and P W equals about 1.39. Scattered circular data points are shown along the plot, including points near P R equals negative 0.76 with P W around negative 0.50, near P R equals negative 0.02 with P W around 0.30, near P R equals 0.72 with P W around 1.00, near P R equals 1.46 with P W around 1.80, and near P R equals 2.21 with P W around 2.60. Note: All numerical data values are approximated.

The moderating impact of job tension. Source: The authors

Figure 3
Two scatter plots show P R, P W relationship, with a stronger positive trend under high job tension.The scatter plots are titled “(Low J T)” on the left and “(High J T)” on the right. In both plots, the horizontal axis is labeled P R and the vertical axis is labeled P W. In the Low J T plot, the horizontal axis shows P R values at negative 1.68, negative 1.03, negative 0.38, 0.26, 0.91, and 1.55. The vertical axis shows P W values at negative 1.25, negative 0.78, negative 0.30, 0.18, 0.66, and 1.14. Multiple circular data points are scattered across the graph, with a lightly sloped fitted line. In the Low J T plot, the fitted line starts near the lower left of the graph at approximately P R equals negative 1.68 and P W equals about negative 0.72, and ends near the upper right at approximately P R equals 1.55 and P W equals about 0.31. Scattered circular data points appear around the line, including points near P R equals negative 1.03 with P W around negative 0.80, near P R equals negative 0.38 with P W around negative 0.30, near P R equals 0.26 with P W around 0.20, near P R equals 0.91 with P W around 0.65, and near P R equals 1.55 with P W around 1.10. In the High J T plot, the horizontal axis shows P R values at negative 1.50, negative 0.76, negative 0.02, 0.72, 1.46, and 2.21. The vertical axis shows P W values at negative 1.25, negative 0.49, 0.28, 1.05, 1.82, and 2.58. The circular data points are more concentrated along an upward-sloping fitted line. The fitted line begins near the lower left at approximately P R equals negative 1.50 and P W equals about negative 0.42, and extends to the upper right ending near P R equals 2.21 and P W equals about 1.39. Scattered circular data points are shown along the plot, including points near P R equals negative 0.76 with P W around negative 0.50, near P R equals negative 0.02 with P W around 0.30, near P R equals 0.72 with P W around 1.00, near P R equals 1.46 with P W around 1.80, and near P R equals 2.21 with P W around 2.60. Note: All numerical data values are approximated.

The moderating impact of job tension. Source: The authors

Close modal

Moreover, the mediation analysis results, as reported in Table 4 above, revealed that PR significantly and positively mediates the relationships between TP and PW (β = 0.206, p < 0.001) and between AS and PW (β = 0.203, p < 0.001). Consequently, H6 and H8 were supported. However, PR does not mediate the relationship between JI and PW (β = 0.008, p = 0.431), thereby rejecting H7.

The next step is to evaluate the model's predictive power using the R2 values for the endogenous variables. The research model explains 38.6% and 34.7% of the variance in the key endogenous variables: PR and PW, respectively. These values signify a substantial level of acceptance (Cohen, 1988). Subsequently, the effect size (ƒ2) is employed to evaluate the predictive accuracy of the endogenous constructs within the sample. Hair et al. (2020) classify effect sizes as small (0.02), medium (0.15), and large (0.35). Table 4 indicates the presence of both medium and large effect sizes, apart from two relationships that exhibit small effects.

Drawing on the JD-R theory, this paper aimed to identify the factors influencing workplace presenteeism. It also explored how presenteeism affects psychological withdrawal, considering the moderating role of job tension in this relationship. The data were collected from employees working in various service sectors in Oman and analysed using PLS-SEM. Overall, most hypotheses are supported.

The empirical results indicated a positive, significant relationship between time pressure and presenteeism. Employees who experience greater time pressure are more likely to engage in presenteeism, attending work despite illness or being less productive. In other words, this relationship suggests that when employees feel rushed or pressed for time, they may be compelled to come to work even when they are not in optimal health, possibly to meet deadlines, complete tasks, or avoid falling behind. This result aligns with previous studies such as Dietz and Scheel (2017), Jia et al. (2022), Ho et al. (2022), and Nordenmark et al. (2019), which reveal a link between time pressure and presenteeism.

The results of the study also demonstrated a positive and significant correlation between presenteeism and abusive supervisors. The likelihood of employees reporting to work despite feeling unwell or unable to perform at their best increases when they encounter abusive behaviour from their supervisors, such as hostility, belittlement, or discriminatory criticism. This conduct may be the result of a variety of factors, including job insecurity, a phobia of additional maltreatment, or a desire to circumvent criticism or unnecessary conflict. This could result in heightened tension and exacerbate health issues, perpetuating a cycle of diminished productivity and worsening health-related problems. These results are consistent with the findings of Lee et al. (2021). Therefore, it is imperative to monitor supervisors' conduct, as an unfavourable work environment can have a detrimental impact on both the organisation and its employees.

Our results also revealed a positive and substantial correlation between presenteeism and psychological withdrawal. The inspiration, fulfilment, and involvement of employees who are either compelled or compel themselves to work while ill are likely to drop. This, in turn, can lead to psychological withdrawal, in which workers show less work dedication and enthusiasm and may mentally withdraw from their job responsibilities. Employees who engage in presenteeism on a regular basis are susceptible to exhaustion and elevated stress levels, which exacerbate their psychological withdrawal. These results are consistent with prior research (Chou and Mach, 2021; Cocker et al., 2013; Silva-Costa et al., 2020), which reported a substantial correlation between presenteeism and psychological withdrawal.

Interestingly, the study's findings did not indicate any correlation between job insecurity and presenteeism. In other words, there was no correlation between employees' propensity to report to work while ill and their fears of losing their employment, and job insecurity did not affect whether employees engaged in presenteeism. This conclusion is in stark contrast to previous research suggesting a stronger correlation between work insecurity and presenteeism, thereby illustrating the variability of study results across contexts (Kim et al., 2020; Schmidt and Pförtner, 2020; Zhang et al., 2020).

The study results also indicate that employment tension plays a substantial moderating role in the association between presenteeism and psychological withdrawal. In other words, the detrimental consequences of presenteeism on psychological withdrawal are exacerbated during periods of elevated job tension. Employees who persist in their employment despite their illness are more susceptible to elevated stress levels, which may contribute to psychological withdrawal. Conversely, in a low-tension work environment, the influence of presenteeism on psychological withdrawal tends to diminish as the stress associated with high workloads and imperative deadlines is alleviated. The emotional and mental detachment from their work is exacerbated by job tension, which increases the detrimental impact of presenteeism on workers' mental health. These findings align with those of Laranjeira et al. (2022), Kim et al. (2019), Jamil et al. (2023), and Wang et al. (2020).

The study results also underline that presenteeism substantially mediates the relationship between psychological withdrawal and time pressure. In simple terms, presenteeism serves as a mediator in the relationship between time constraint and psychological withdrawal. Employees are more likely to be involved in presenteeism and work while ill when they are subjected to increased time pressure, which results in psychological withdrawal. High stress levels, fatigue, and exhaustion may result from presenteeism, which is likely to lead to greater psychological withdrawal from work if employees are compelled to participate due to time constraints.

The results also indicated that presenteeism substantially mediates the relationship between psychological withdrawal and an abusive supervisor. Employees are more likely to participate in presenteeism when they are subjected to oppressive supervision that requires them to report to work despite being ill. This behaviour can be a coping mechanism or a response to fear of further abuse or job loss. As a result, this increased presenteeism, driven by the abusive supervision, leads to higher levels of psychological withdrawal, where employees emotionally and mentally disengage from their work due to the compounded stress and reduced well-being. Essentially, presenteeism serves as a bridge through which the negative impact of abusive supervision is translated into psychological withdrawal.

Our results highlight an insignificant mediating role of presenteeism on the relationship between job insecurity and psychological withdrawal. This means that the study found that presenteeism does not significantly influence or alter the relationship between job insecurity and psychological withdrawal. In other words, even when employees who feel insecure about their jobs engage in presenteeism, this behaviour does not notably affect their tendency to withdraw psychologically from their work. This suggests that other factors might be more influential in linking job insecurity to psychological withdrawal than presenteeism (Li, 2023).

Although no prior studies have examined the mediating role of presenteeism in these connections, our results generally support findings from past research highlighting presenteeism's mediating role across different connections, such as Deery et al. (2014), Ning et al. (2023), and Zhang et al. (2020). In sum, findings highlight that presenteeism is not a marginal or isolated behaviour but a systemic phenomenon at the intersection of process design, organisational efficiency, and leadership practices. Addressing it requires integrated HR and operations strategies that prioritise employee well-being while safeguarding organisational performance.

From a theoretical perspective, the findings extend the JD-R framework by conceptualising abusive supervision not merely as a relational challenge but as a persistent job demand that induces presenteeism and subsequently psychological withdrawal. In doing so, the study broadens the scope of JD-R theory, showing that leadership behaviours must be incorporated alongside structural job demands such as time pressure. Furthermore, the results emphasise presenteeism's mediating role between demands—such as time pressure and abusive supervision—and withdrawal, thereby highlighting its key function as a behavioural mechanism that converts workplace stressors into decreased employee engagement. The moderating effect of job tension adds nuance, showing that presenteeism is not a uniform phenomenon but intensifies under heightened stress. Collectively, these contributions enrich scholarly understanding of presenteeism as both an outcome of workplace design and leadership practices and as a driver of disengagement, inefficiency, and reduced organisational resilience.

Theoretically, this model helps deepen understanding of how organisational and individual factors interact to influence employee behaviour, emphasising the pathways through which variables such as job insecurity, supervisory behaviour, and psychological withdrawal can lead to outcomes such as presenteeism. It offers a framework for future research to examine these relationships in diverse organisational settings and confirms the importance of integrating psychological and organisational theories. Managerially, the research provides practical guidance for organisations aiming to reduce negative workplace behaviours and boost productivity.

By identifying key causes of presenteeism, managers can create targeted interventions, such as improving supervisor support, addressing job insecurity, and promoting employee engagement, ultimately supporting both employee well-being and organisational performance.

As underlined above, our findings also carry substantial implications for strategic HRM and operations management.

From a process design and workload management perspective, presenteeism should be treated as a signal of systemic inefficiency. When employees regularly work while unwell, this often reflects poor task allocation, excessive time pressure, or inflexible processes. Redesigning workflows through lean management, optimising staffing levels, and implementing realistic scheduling can reduce chronic time pressure and alleviate the factors that drive presenteeism.

From a leadership development and accountability perspective, abusive supervision emerged as a critical antecedent of presenteeism. Organisations must therefore prioritise leadership development programs that foster supportive, ethical, and emotionally intelligent supervisory practices. Leadership accountability mechanisms, such as incorporating employee well-being indicators into managerial performance appraisals, can further ensure that supervisory behaviours enhance rather than undermine organisational efficiency.

Considering health, well-being, and HR policies, presenteeism undermines both employee health and service quality. HR strategies should thus embed proactive well-being initiatives, such as employee assistance programs, wellness resources, and flexible sick-leave policies. By reducing the stigma of absence and providing accessible health support, organisations can prevent the escalation from short-term presenteeism to long-term disengagement and burnout.

Employing an integrated HR-operations monitoring can also represent a winning strategy. Indeed, presenteeism metrics should be incorporated into HR dashboards and operational performance reviews, allowing organisations to identify patterns that compromise efficiency. By linking HR analytics to operational outcomes (for instance, service errors, delays, or customer complaints), managers can treat presenteeism as an early warning system for organisational inefficiency.

Last but not least, in service industries, where human capital is the core resource, reducing presenteeism is both a health imperative and a strategic priority. By aligning HR policies with operational redesign, firms can enhance employee engagement, safeguard service quality, and build sustainable competitive advantage.

While our results may look promising and could lead to some practical suggestions to enhance job's sustainability, our study has some limitations which should be acknowledged. Data was collected from only one country (namely Oman), and some specific business fields were selected. Such aspects may have biased some of our results, as cultural elements may impact how people engage in their work duties. This may also be affected by the investigated service sectors. For instance, the tourism and hospitality fields often experience a peak timeframe, when high workloads may scare or stress workers, leading to presenteeism. Such aspects may be less evident in fields where the usual workloads are better programmed and managed from an organisational perspective. Such limitations may be overcome by enlarging the number of countries enquired and respondents, as well as the variety of business fields investigated. Concentrating on limited geographical or industrial samples may require a better understanding of the eventual cultural attitudes to work and the existing labour regulations (such as sick and parental leave policies, number of days off, work flexibility opportunities, eventual rewards, and how they are assigned …). Similarly, researchers might look at cross-industries instead of just the services sector, where absenteeism in these areas affects how work is done in organisations.

Moreover, while a quantitative approach may help generalise and measure the phenomenon, in-depth qualitative research methods, such as interviews, may allow for a better understanding of the dynamics, supporting employers and policymakers in defining regulations to increase the well-being of their workers, as well as their performance. Such aspects may represent new and exciting research avenues in the field.

Since the current study used non-probability sampling techniques, future research could utilise probability sampling methods to improve representativeness and generalisability.

Future studies should critically explore other potential moderators and mediators beyond those examined in this paper. These include different leadership styles, organisational support, organisational justice, pathways to burnout, and other corporate practices that may either increase or reduce presenteeism. Future research could also explore the relationship between positive work-related factors, such as transformational leadership, employee motivation, and involvement (Al-Aamri et al., 2024), and their potential influence on employee presenteeism. Besides, researchers should provide cross-cultural empirical evidence; for example, work characteristics such as demands and organisational support have different effects across sectors and populations. The research requires further investigation to examine how personal characteristics, along with demographic factors and cultural factors such as age, gender, and organisational culture, influence the results.

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