2024 Volume 46 Issue 4 Pages 275-282
Presenteeism, a detriment to productivity, is theorized to be associated with work engagement. However, this relationship remains unexplored among Indonesian manufacturing workers. This study aimed to determine the relationship between work engagement and presenteeism in heavy equipment manufacturing workers. This cross-sectional study collected data from 109 workers employed at a heavy equipment manufacturing firm in Jakarta, Indonesia. Presenteeism was evaluated through the Quality and Quantity (QQ) method questionnaire, and work engagement was assessed using the Indonesian version of the Utrecht Work Engagement Scale 9 (UWES-9) questionnaire. Respondents exhibited high work engagement score (median = 5.55) and low presenteeism score (median = 10), showing a significant negative correlation (r = –0.381) between the two. The high work engagement observed among heavy equipment manufacturing workers in Indonesia correlates with a low occurrence of presenteeism.
Presenteeism refers to a condition that can negatively affect productivity, whereby the state of presenteeism will reduce or even eliminate the productivity of individuals and companies in general [1]. A previous meta-analysis study across 14 countries showed a substantial prevalence of presenteeism among nurse workers, at 49.2%, with variations in different reporting timeframes [2]. Another study stated that the prevalence of presenteeism events among Industrial sector workers reached 57.6% [3]. These studies demonstrate that presenteeism is one of the issues that needs to be addressed in the field of occupational health.
Presenteeism is a relatively new concept, and some research argues that presenteeism has two main definitions [4–6]. Ishimaru and Aronsson define presenteeism as ‘sickness presenteeism’, which refers to the condition where an individual has health complaints that warrant rest and absence from work, but still goes to work regardless [5, 7]. Another definition, termed ‘work function impairment’, is defined as the state where there is ‘decreased on-the-job performance, for reasons other than illness’ [5, 7, 8]. Regardless of its definition, presenteeism has been shown to significantly predict productivity loss, as referenced in previous studies [9].
Several previous studies have indicated that job-related factors have the greatest influence on presenteeism [10, 11], specifically high job demands and inadequate job resources (for example, having too much to do but insufficient time in which to do it, inadequate support, and insufficient technological resources) [11]. Presenteeism occurs most frequently among those aged 30–49 years [11], females and separated/divorced/widowed employees [11, 12]. Administrative/office workers and service workers have also been noted to have higher presenteeism [10].
A study conducted in England found that perceptions of high job demand increased self-reported risks of presenteeism, while control over aspects of the job and support from managers and co-workers tended to prevent this occurrence [13]. Previous studies in Korea have also found that presenteeism was significantly higher among workers with the following characteristics: working over 40 hours per week, shift workers, those with high quantitative job demands, low job autonomy, high emotional demands, and high job stress [14].
The Job Demand-Resource (JD-R) model assumes that every job has its own characteristics, which are categorized into two groups: job demands and job resources. Job strain occurs when there are high job demands but limited job resources. Work engagement is more likely to happen when job resources are high. Work engagement is therefore an important predictor related to mental health and productivity in the workplace, as it describes a state in the work environment that has a positive influence on workers [15, 16]. Schaufeli et al defined work engagement as a positive, satisfying, work-related state of mind characterized by vigor, dedication, and absorption [17–19].
A study using the JD-R model investigated how work engagement can mediate the relationship between emotional exhaustion and productivity loss from presenteeism [20]. The results of that study stated that emotional exhaustion positively predicted productivity loss from presenteeism, while work engagement negatively predicted productivity loss. The study also found that, on a daily level, work engagement mediated the impact of emotional exhaustion and negative effects on productivity loss from presenteeism [20]. Another study yielded similar results, where employees with high levels of work engagement had significantly lower health risk factors and presenteeism levels compared to employees with moderate or low levels of work engagement [21]. Evidence from a previous study has shown that individuals who exhibit lower levels of job satisfaction and engagement are more likely to report presenteeism [22].
This research aims to investigate the relationship between work engagement and presenteeism among heavy equipment manufacturing workers in Indonesia. To our knowledge, no similar studies have been conducted within the Indonesian working population, particularly from a standpoint of occupational medicine. This study focuses specifically on industrial workers, a substantial demographic in Indonesia, to provide initial insights into these issues within this specific context. Investigating the association between socioeconomic status and both work engagement and presenteeism constitutes a secondary aim of this study.
This cross-sectional study was conducted at a heavy equipment manufacturing company in Jakarta, Indonesia, with a total of 110 respondents who met the inclusion criteria of being full time workers (not freelancers, consultants, etc.) and having worked for at least 1 year. The population sample, obtained through simple random sampling from a list of 1,800 employees, required a minimum of 85 participants based on the correlation assessment formula (minimum correlation coefficient of 0.3). Adjusting for an anticipated 10–20% dropout rate, we settled on a final sample size of 110 individuals. Data collection took place in mid-November 2023 and concluded within 10 working days. Prior to the study’s commencement, participants were briefed on its objectives, screened for eligibility, and provided informed consent. Each participant received a 20-item questionnaire, which was distributed manually and typically took about 10 minutes to complete.
Presenteeism was assessed using the Quality and Quantity Method (QQ method) questionnaire which referred to previous studies on presenteeism [23, 24]. The QQ method assessment commenced by inquiring whether participants had encountered any health issues during their work within the preceding month. If respondents replied in the negative, presenteeism was recorded as zero. Conversely, if participants answered affirmatively, they were prompted to select their primary health concern from a roster of 14 conditions, pinpointing the one that exerted the most significant impact on their job performance [23, 24]. If the health condition did not impact their work, presenteeism was likewise recorded as zero. Following this, participants were prompted to elucidate how their work varied in terms of Quality and Quantity during episodes of health issues compared to when they were in good health. Responses were graded on a scale from 0 (unable to work) to 10 (normal productivity). The presenteeism score was computed using the subsequent formula [23, 24]:
presenteeism score = 100 – quantity (range: 0–10) × quality (range: 0–10)
Work engagement was measured using the Indonesian version of the 9-item Utrecht Work Engagement Scale (UWES-9), which has been validated and shown to be reliable with a Cronbach’s alpha of 0.85 [25]. The UWES-9 consists of 9 questions related to work engagement with a Likert scale of 0 – 6. Scoring was done by summing the scores for all the questionnaire items and dividing by the number of items in the questionnaire [17].
The covariates consisted of age, sex, marital status, type of work, pattern of work and duration of work in a week. Age was categorized into ‘less than 40 years old’ and ‘40 years old or older’, based on previous studies which indicate that individuals aged 40 years or older tend to exhibit higher levels of presenteeism [10, 14]. Marital status was categorized as married, single/not married, or divorced. The type of work was classified as either office-based or factory-based. Work pattern was categorized into shift or non-shift work. Work duration was categorized into whether the respondent worked more than 40 hours per week or less. This classification was guided by past studies that indicated a higher prevalence of presenteeism among those working over 40 hours weekly [14].
Bivariate correlation analysis was carried out to see the relationship between work engagement scores and presenteeism scores, which were presented in the form of numerical data. The relationship between sociodemographic variables and presenteeism was analysed using the Mann-Whitney U test and the Kruskal-Wallis test. To assess the strength of the relationship between work engagement and presenteeism, while controlling for respondents’ sociodemographic characteristics, a linear regression analysis was conducted. This analysis was informed by the results of bivariate analyses and subsequent stepwise regression. This research was approved by the Health Research Ethics Committee, Faculty of Medicine, University of Indonesia – Cipto Mangunkusumo National Government General Hospital with number KET-1564/UN2.F1/ETIK/PPM.00.02/2023.
Out of the 110 respondents that filled in the questionnaire, one respondent did not fully answer the questions and was excluded from further analysis. Therefore, the total number of respondents analysed was 109. All of the respondents (100%) were male, and 57 of them (52.3%) were under 40 years old. Most of the respondents (80.7%) were married, and 64 respondents (58.7%) worked shift schedules. A total of 82 respondents (75.2%) worked in a factory, and 66 respondents (60.6%) worked over 40 hours per week. Details are shown in Table 1.
| Variable | n | % |
|---|---|---|
| Age | ||
| < 40 years old | 57 | 52.3 |
| ≥ 40 years old | 52 | 47.7 |
| Sex | ||
| Male | 109 | 100 |
| Female | 0 | 0 |
| Marital Status | ||
| Married | 88 | 80.7 |
| Single / not married | 20 | 18.3 |
| Divorce | 1 | 0.9 |
| Type of Work | ||
| Office | 27 | 24.8 |
| Factory | 82 | 75.2 |
| Work Pattern | ||
| Shift | 64 | 58.7 |
| Non-Shift | 45 | 41.3 |
| Work Duration (hours per week) | ||
| ≤ 40 hours | 43 | 39.4 |
| > 40 hours | 66 | 60.6 |
The results of the assessment of the respondents’ work engagement show that most of them had high work engagement scores with a median value of 5.55 (minimum 3.33 and maximum 6.00). Meanwhile, the total presenteeism scores of the respondents were relatively low, with a median presenteeism score of 10 (reference scale 0-100), with a minimum value of 0 and a maximum of 76.
Another finding in this research is related to the relationship between work engagement scores based on sociodemographic characteristics. It is known that the factors of work type and work pattern have a significant relationship with work engagement with each P value <0.001. Details are shown in Table 2.
| Variable | Work Engagement Score | |||
|---|---|---|---|---|
| Median | Q1 | Q3 | P value | |
| Age | ||||
| < 40 years old | 5.55 | 5.00 | 5.78 | 0.476* |
| ≥ 40 years old | 5.55 | 5.02 | 5.89 | |
| Marital Status | ||||
| Married | 5.55 | 5.00 | 5.89 | 0.241** |
| Single / not married | 5.38 | 5.02 | 5.72 | |
| Divorce | – | – | ||
| Type of Work | ||||
| Office | 5.22 | 4.67 | 5.33 | <0.001** |
| Factory | 5.66 | 5.22 | 5.89 | |
| Work Pattern | ||||
| Shift | 5.77 | 5.13 | 5.97 | <0.001* |
| Non-Shift | 5.33 | 4.89 | 5.56 | |
| Work Duration (hours per week) | ||||
| ≤ 40 hours | 5.55 | 5.00 | 5.78 | 0.936* |
| > 40 hours | 5.55 | 4.89 | 5.89 | |
*Mann-Whitney U test; **Kruskal-Wallis test
The tests revealed that age, marital status, and weekly working hours were not significantly associated with presenteeism (P value > 0.05). In contrast, work pattern had a highly significant association (P value <0.001). While work type initially showed no significant relationship (P value of 0.198), the multivariate analysis later demonstrated that it was in fact significantly related to presenteeism (P value 0.013). Details are shown in Table 3.
| Variable | Presenteeism Score | |||
|---|---|---|---|---|
| Median | Q1 | Q3 | P value | |
| Age | ||||
| < 40 years old | 10 | 0 | 44 | 0.885* |
| ≥ 40 years old | 10 | 0 | 36 | |
| Marital Status | ||||
| Married | 10 | 0 | 36.75 | 0.639** |
| Single / not married | 5 | 0 | 49.25 | |
| Divorce | 0 | 0 | 0 | |
| Type of Work | ||||
| Office | 19 | 0 | 51 | 0.198* |
| Factory | 0 | 0 | 36 | |
| Work Pattern | ||||
| Shift | 0 | 0 | 19.75 | 0.001* |
| Non-Shift | 36 | 0 | 51.00 | |
| Work Duration (hours per week) | ||||
| ≤ 40 hours | 10 | 0 | 37 | 0.992* |
| > 40 hours | 5 | 0 | 44 | |
*Mann-Whitney U test; **Kruskal-Wallis test
The results of bivariate correlation analysis, as shown in Figure 1, revealed a significant negative correlation between work engagement and presenteeism with P value < 0.001 and correlation coefficient (r) –0.381. This study reveals that heightened levels of work engagement are associated with diminished occurrences of presenteeism.
Based on the results of bivariate analysis and subsequent stepwise regression, it was determined that only the covariates “type of work” and “work pattern” exhibited statistically significant correlations with the incidence of presenteeism, thereby meeting the criteria for inclusion in the multivariate analysis. The results of the linear regression test showed that work engagement was related to presenteeism (P value <0.001) after controling for work type and work pattern factors. The R square of this linear regression model was 26%. The factor that most strongly related to presenteeism was work engagement (P <0.001), followed by work pattern (P = 0.001) and work type (P = 0.013). Details are shown in Table 4.
| Parameter | Parameter Estimate | Standardized Coefficients Beta | 95% CI | P value |
|---|---|---|---|---|
| (Constant) | 64.549 | 17.885 – 1112.213 | 0.007 | |
| Work Engagement Score | –17.919 | –0.431 | –25.453 – (–10.385) | <0.001 |
| Type of Work | 17.751 | 0.274 | 7.915 – 27.587 | 0.013 |
| Work Pattern | 14.939 | 0.371 | 3.248 – 26.631 | 0.001 |
This study shows a significant negative correlation between work engagement and presenteeism, confirming previous findings by Burton [21], who observed that higher work engagement correlates with reduced presenteeism. Côté et al also suggested that decreased work engagement contributes to employees’ presenteeism behaviours [22]. According to the Job-Demand Resource model, high work engagement typically occurs in environments with sufficient job resources [15, 16]. These resources enable employees to effectively manage psychological pressures and reduce work-related stress, factors strongly linked to lower levels of presenteeism [14].
This study underscores the assertion that fostering high levels of work engagement can play an important role in potentially reducing presenteeism among employees. When employees are highly engaged in their work, they demonstrate a strong commitment and dedication to their roles, which can lead to several beneficial outcomes that mitigate presenteeism. First, employees with high work engagement are more likely to maintain good health behaviours and self-care practices. They are motivated to stay physically and mentally fit, reducing the likelihood of health issues that might lead to absenteeism or presenteeism [21].
Secondly, high levels of work engagement contribute to a positive work environment characterized by increased job satisfaction and lower stress levels [26]. One of the elements that facilitates achieving high work engagement is the presence of effective job resources, such as a supportive work environment that emphasizes job control and support from managers and colleagues to mitigate presenteeism [13]. Employees who have control over their tasks experience lower stress levels and can manage their workload effectively. This empowerment enables them to prioritize health and well-being, and to make informed decisions about breaks and medical care, thereby reducing presenteeism.
Our findings align with a meta-analysis study by Mori et al, which identified that one of the main factors related to presenteeism was job-related factors [23]. Focusing on job resources, which are part of the JD-R model, these job factors are known to influence health through work engagement. Thus, job-related psychological states such as work engagement and job satisfaction reduce presenteeism [23]. Further exploration into specific job resources and their impact on work engagement and presenteeism can offer deeper insights into effective interventions for addressing these issues in occupational settings.
This study also examined several factors that influence presenteeism among heavy equipment manufacturing workers in Indonesia. Age and marital status were found not to significantly correlate with presenteeism, despite previous research suggesting higher levels among older [10, 14, 27] and divorced individuals [10]. Work type initially showed no significant relationship, but was later found to be significantly associated with presenteeism in the multivariate analysis, aligning with findings of elevated presenteeism in occupations with high quantitative job demands [14]. Our respondents, categorized as factory-based workers, operate within defined timeframes, engage in physical labour, and aim to achieve specified productivity goals, reflecting a significant emphasis on quantitative job demands—defined as aspects of work involving the amount and speed of tasks, requiring both physical and psychological effort [28].
Shift patterns (shift vs. non-shift) demonstrated a significant association with presenteeism. Shift workers in this study exhibited lower median presenteeism scores, contrary to previous studies that stated otherwise [2, 14]. This phenomenon was possibly due to higher work engagement in shift workers group, but the exact mechanisms require further investigation. Additionally, work duration did not exhibit a statistically significant correlation with presenteeism in this study, contrasting with prior research linking longer work hours to increased presenteeism [6, 14]. The minimal additional work hours reported by participants may explain this lack of significant association.
In addition to the bivariate analysis showing a moderate negative correlation (r = –0.381) between Work Engagement and Presenteeism, our multivariate analysis revealed significant associations between presenteeism and variables such as type of work and work pattern. These findings underscore the multifaceted nature of factors influencing presenteeism among heavy equipment manufacturing workers in Indonesia. Moreover, our linear regression model demonstrated that these variables collectively explain approximately 26% of the variance in Presenteeism (R2 = 0.26). This suggests that while Work Engagement plays a significant role, the type of work and work pattern also contribute substantially to the occurrence of presenteeism in this population. These results provide valuable insights into the complex interplay of work-related factors affecting employee presence at work despite health issues, emphasizing the need for targeted interventions to mitigate presenteeism among industrial workers.
This study’s limitations include limited sample heterogeneity regarding respondent characteristics, sole focus on the correlation between work engagement and presenteeism without group comparisons or analysis of influencing factors within job characteristic groups, and potential lack of generalizability to the broader manufacturing worker population in Indonesia due to the exclusive focus on one company.
However, this study also has notable strengths. To our knowledge, it provides initial data on work engagement and presenteeism distributions among heavy equipment manufacturing workers in Indonesia. Additionally, it is the first investigation of the relationship between work engagement and presenteeism within this worker population. Thus, it offers a valuable starting point for understanding work experiences in Indonesian heavy manufacturing, despite the aforementioned limitations.
Future research should encompass a larger, more diverse sample size and include additional variables to enhance understanding of the relationship between work engagement and presenteeism. Further investigation into the underlying characteristics of these constructs among heavy equipment manufacturing workers is warranted to elucidate our discrepancies with previous studies. This study underscores the significance of adequate job resources in fostering high work engagement to mitigate job demands associated with presenteeism. Its findings can inform the development of employee engagement programs aimed at addressing productivity challenges, particularly presenteeism, within companies.
In this study of heavy equipment manufacturing workers in Jakarta, Indonesia, high levels of work engagement were observed alongside low rates of presenteeism. The research identifies a significant negative correlation between work engagement and presenteeism, highlighting work engagement as the predominant predictor compared to Type of Work and Work Pattern, both of which also exhibited significant correlations with presenteeism. These findings emphasize the critical role of promoting work engagement to mitigate presenteeism among industrial workers.
We would like to express our gratitude to all parties who supported this research. The completion of this study was made possible through the assistance and contributions of several individuals and institutions.
The authors declare no conflict of interest. All authors contributed sufficiently to the study and agreed with the results and conclusions.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
