Abstract
BACKGROUND:
Work-related fatigue is common among automobile factory employees.
OBJECTIVES:
The purpose of this study was to assess fatigue of employees at a Chinese automobile factory.
METHODS:
238 employees (119 engineers and 119 workers) participated in this study. The following questionnaires were completed: demographic survey questionnaire, working condition questionnaire (WCQ), functional assessment of chronic illness therapy-fatigue (FACIT-F), subscales of multidimensional fatigue inventory (MFI), and Pittsburgh sleep quality index (PSQI).
RESULTS:
Both engineers and workers experienced fatigue. The workers (35.6 years old, SD = 6.7) generally felt more fatigue than engineers (42.6 years old, SD = 6.4). The engineers claimed to be more satisfied with the working conditions than workers. The WCQ showed good properties for assessing work-related factors, which were significantly correlated with fatigue (r = 0.568 for engineers and r = 0.639 for workers). For engineers, general fatigue was observed regularly and frequently, and for workers, physical fatigue usually had a long duration.
CONCLUSIONS:
The fatigue was significantly correlated with work-related factors, especially working environment and monotony. For workers, the duration of the work day also affected their fatigue. Some improvements to the working condition in this automobile factory should be considered.
Introduction
Fatigue is an essentially subjective experience, and it is typically defined as extreme and persistent weariness, weakness, or mental or physical exhaustion [1, 2]. Work-related fatigue is related to occupational health. It can have serious maladaptive effects on the health of the working population. It can even cause chronic disease. Most individuals report feeling fatigued during work hours, especially after poor sleep or inadequate rest, after physical exertion, or after pronounced mental effort [3].
Work-related fatigue is considered a cause of occupational injury in most industrialized countries. Within the European community, 40% of workers are reported to experience significant fatigue [4, 5]. Similar cases have been reported from Norway [6], Canada [7], the United States [8], Sweden [9], and Japan [10, 11]. Work-related fatigue can affect occupational health and safety, personal well-being, and even national and personal productivity.
With the boom of industrial automation in China, automated equipment has been widely introduced in the manufacturing industry, especially in automobile factories. The amount of manual work has been decreased, and the jobs remaining for people are mostly monotonous and repetitive and commonly involve low workload. They may include monitoring the running of equipment, data entry, and assembly line work. It is well documented that monotonous and repetitive work can increase bodily pain (such as that of the lower back, shoulder, or neck) and mental weariness [12–15]. Aronsson et al. found the prevalence of neck and shoulder symptoms to be twice as high among workers involved in monotonous data entry work than among programmers and system operators [16]. Finally the symptoms could develop into physical or psychological disease, such as musculoskeletal disorders and chronic fatigue syndrome (CFS) [17]. Work-related fatigue is considered a common problem in the general population. It has been reported that about 142–560 persons per 1,000,000 adults in the United States experience prolonged fatigue, and the prevalence is higher among non-white persons [18]. In Japan, 60% of working people say they had felt “extreme fatigue” [19]. In China, more than 700,000,000 people have impaired health, with chronic fatigue as one of the main symptoms [20]. However, work-related fatigue is easy to overlook in automobile factories, because the tasks usually involve low workload. When people finally recognize their health problems after long-term fatigue, it maybe that its cumulative effect on health has already become serious and irreversible.
As the wellbeing of employees is of crucial interest to organizations [21], the specific fatigue status of the employees and the factors that induce fatigue should be studied. There are many factors that influence work-related fatigue, such as sleep debt, psychological distress, health perception, work conditions, personal characteristics and so on [22–25]. It was reported that people doing different jobs might have different feelings of fatigue even in same workplace [26], and people with different gender also performed differently [27]. Therefore, in our study, we compared the data from different job categories (engineers and workers) and gender.
Muscular fatigue is a common phenomenon for physical activities at work [28], therefore, repetitive work is usually defined by physical work characteristics, for example, upper extremity movements. Work-related fatigue caused by repetitive work usually straightforward attributed to mechanical tissue overload related to repetitive movements, force requirements, and awkward postures, but it is inherently correlated with psychosocial factors [29]. Psychological scales may offer a valid way to assess fatigue and its factors. This study, therefore, was to use subjective measures to assess work-related fatigue among automobile factory employees. A new working condition questionnaire was developed to assess work-related factors.
Methods
The survey was conducted among the employees of an automobile factory, and a package of questionnaires was handed out to measure different aspects associating with fatigue.
Participants
To assess the work-related fatigue among automobile factory employees, 260 employees (130 engineers, 130 workers) were enrolled in the study from December 2014 to May 2015. Participants were eligible if they met the following criteria: 1) healthy, no severe disease, 2) performing repetitive and monotonous tasks, and 3) willing to participate. Fifty-five participants completed the scales again four weeks later to confirm the test-retest reliability of the working condition questionnaire.
Questionnaire
A large number of scales have been developed attempting to measure the nature, severity, and impact of fatigue in a range of different populations. Dittnera et al. collected seven published scales of fatigue assessment for general populations: fatigue severity scale (FSS), checklist individual strength (CIS), fatigue questionnaire (FQ), multidimensional fatigue inventory (MFI), piper fatigue scale (PFS), visual analogue rating of physical energy and mental energy (PE and ME), and functional assessment of chronic illness therapy-fatigue (FACIT-F) [30]. Several measures of fatigue in patient populations have also been suggested as useful in healthy individuals [31]. MFI and FACIT-F had already been examined and found to have good psychometric properties in the Chinese population [32, 33]. Some researchers have asserted that fatigue is best conceived of as a multidimensional construct [34]. For instance, one person might feel physically exhausted and mentally alert, while a second might feel mentally tired but physically fit. In this way, the items used for measuring physical and mental fatigue were taken from the MFI, and general fatigue was measured using FACIT-F. Surveys of quality of life, sleep quality, demography characteristics, and working conditions were also carried out.
Multidimensional Fatigue Inventory (MFI)
The MFI is a self-report instrument designed to measure fatigue [3]. It covers five dimensions: general fatigue, physical fatigue, mental fatigue, reduced motivation, and reduced activity. Each dimension could be used as a single subscale. Higher scores indicate a higher degree of fatigue. This instrument was tested for its psychometric properties in cancer patients, patients with chronic fatigue syndrome, psychology students, medical students, army recruits, and junior physicians. Physical fatigue and mental fatigue served as indicators of physical and mental fatigue, respectively.
Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F)
The FACIT-F is a self-reported scale with one dimension. It was developed to assess fatigue associated with cancer anemia [35]. Overall scores of the FACIT-F scale range from 0 to 52, with higher scores signifying less fatigue. It has been widely used in various Western populations, including general populations [36], patients with psoriatic arthritis [37], rheumatoid arthritis [38], Parkinson’s disease [39], systemic lupus erythematosus [40], and Chinese patients on maintenance dialysis [41]. It has shown excellent psychometric properties and strong correlations with other fatigue measurement tools. Authorization to use our Chinese translation of the FACIT-F tool was obtained from the FACIT organization.
Pittsburgh Sleep Quality Index (PSQI)
The PSQI is a questionnaire that assesses sleep quality [42]. It includes seven components: subjective sleep quality; sleep latency; sleep duration; habitual sleep efficiency; sleep disturbances; use of sleeping medication; and daytime dysfunction. Higher scores represent poorer sleep quality. It is generally accepted that fatigue and fatigue-related impairment are influenced by prior sleep history, and reduced sleep, increased wakefulness, and longer work hours could produce work-related fatigue [43, 44]. The working conditions are also believed to be related to sleep [45]. The Chinese version of the PSQI has shown good reliability and validity in a general population, as evaluated by Liu et al. [46].
Demographic survey questionnaire
The demographic survey questionnaire was developed here to determine the demographic characteristics of participants in the current study. It has ten items, including gender, age, type of work, shift work, and some self-reported items addressing fatigue and bodily health.
Working Condition Questionnaire (WCQ)
The dimensions of WCQ were constructed according to working features of the automobile factory. There were four work-related factors: workload, duration of work day, working environment, and monotony. Items were worded in a positive and a negative direction to prevent tendencies towards the response set. Each item was scored from 1 (strongly agree) to 5 (strongly disagree). Negative items were scored in reverse, and higher total scores indicated better working condition. The items on this questionnaire are listed in Table 1. The psychometric properties of WCQ were tested in this study, and it showed good reliability and validity for use with the intended population of this study.
Items of Working Condition Questionnaire
Items of Working Condition Questionnaire
NOTE: WL = Workload, WT = Working time, M = Monotony, WE = Working environment.
The WCQ was developed to assess the working conditions of participants in this study. According to the data analysis, it had strong internal consistency and test-retest reliability with an average Cronbach’s alpha of 0.890 and an intraclass correlation coefficient (ICC) of 0.959 (95%: 0.929, 0.976). For engineers and workers, the Cronbach’s alphas were 0.902 and 0.862, respectively (P < 0.01).
The validity of WCQ content was determined using the content validity index (CVI) of 0.780–1.000. The universal agreement and average agreement of Scale-CVI were 0.808 and 0.960, respectively. The validity of the construct was tested using principal components analysis (PCA). The KMO value was 0.787 and Bertlett’s Test of Sphericity was significant (P < 0.01). Data analysis showed a four-factor solution. After varimax rotation, four factors were found to clearly represent different dimensions, here defined as workload, working time, working environment, and monotony, see Table 2.
Factor Labels and Variance
Factor Labels and Variance
Before measurement, the participants received an information sheet describing the study and informed consent. Those who provided informed consent then received a complete package of measurement tools. Then participants were asked to complete the package of measurement tools: the subscales of MFI were used to measure physical and mental fatigue, the FACIT-F to measure general fatigue, the PSQI to measure sleep status, the demographic survey questionnaire to determine participants’ characteristics and the WCQ to measure working conditions. Participants completed these surveys at their workplace in the morning before work starting.
Statistical analysis
All statistical analyses were conducted using SPSS 18.0 (SPSS, Inc., Chicago, IL, U.S.). Continuous variables are expressed as mean (standard deviation (SD)). Categorical variables are expressed as relative frequencies. Levels of significance were set to P-value below 0.05, except where otherwisespecified.
Results
Participants’ characteristics
Of the 260 employees, 22 (8%) had missing data, Hence, 238 (119 engineers and 119 workers) with complete data were eligible for analysis. The groups of engineers and workers showed significant differences on variables of age, gender, marital status, service year and health condition, see Table 3. The average age of all samples was 29.4 (SD = 5.3). The engineers (31.1, SD = 5.3) were generally older than workers (27.7, SD = 4.3). More men (85.3% men, 14.7% women) were surveyed because there were more male employees. The majority of the engineers (58.8%) were married, while the majority of workers (70.6%) were single. The average length of employment at this factory was 4 years (SD = 2.3). About half (51.4%) reported themselves to be in very good health.
Participants’ Characteristics (n = 238)
Participants’ Characteristics (n = 238)
NOTE: aT test for independent samples; b X2 test.
See Table 4, the mean scores of FACIT-F were significantly different between engineers (42.6, SD = 6.4) and workers (35.6, SD = 6.7). The workers reported more fatigue than engineers in general. For engineers, women (40, SD = 5.4) experienced more fatigue than men (43.5, SD = 6.7). Among workers, men (35.5, SD = 6.1) experienced more fatigue than women (38, SD = 6.9). Physical and mental fatigue showed no significant differences between men and women or between engineers and workers. However, unlike earlier assessments, workers (15.4, SD = 2.4) reported more mental fatigue and engineers (15.7, SD = 3.4) reported more physical fatigue. Men showed higher mean scores on both physical and mental fatigue than women. The majority of engineers (64.7%) reported experiencing fatigue recently. Most of the employees (76.5% engineers, 58.8% workers) reported fatigue once every one or two months but recovered quickly. Based on the PSQI, the engineers experienced better-quality sleep than workers.
Scores of FACIT-F, Physical fatigue, Mental fatigue, WCQ, PSQI, and Prolonged Fatigue Items (n = 238)
Scores of FACIT-F, Physical fatigue, Mental fatigue, WCQ, PSQI, and Prolonged Fatigue Items (n = 238)
NOTE: aT test for independent samples; b X2 test.
The mean score of WCQ also differed significantly between engineers and workers. The engineers were more satisfied with the working conditions. Women had higher mean scores than men in general. Higher scores meant better assessments of the working conditions.
The mean score of WCQ showed positive correlations with the FACIT-F score (r = 0.568 for engineers; r = 0.639 for workers), and negative correlations with PSQI(r = –0.581 for engineers; r = –0.558 forworkers).
For engineers, general fatigue, physical fatigue, and mental fatigue were all significantly correlated with the work-related factors of working environment and monotony. Self-reported health condition showed a significant correlation with physical fatigue. On the indexes for predicting prolonged fatigue, the item of “Felt fatigue in the last six months” was significantly closely correlated with all types of fatigue and sleep quality, “Duration of fatigue” was correlated with general fatigue (Table 5-1).
Correlation between Fatigue, Sleep Quality, and Related Factors (engineers, n = 119)
Correlation between Fatigue, Sleep Quality, and Related Factors (engineers, n = 119)
NOTE: **P < 0.01; *P < 0.05.
Correlation between Fatigue, Sleep Quality, and Related Factors (workers, n = 119)
NOTE: **P < 0.01; *P < 0.05.
For workers, significant correlations were observed between general fatigue and sleep quality and working time, physical fatigue and monotony, and mental fatigue and working environment. Self-reported health condition showed a significant correlation with mental fatigue, which differed from the engineers’ data. On the indexes that predicted prolonged fatigue, the item “duration of fatigue” showed a significant correlation with physical fatigue (Table 5-2).
At present, repetitiveness and monotonous work are common in industries with automated work processes [47]. Especially in China, working in an automobile factory has become repetitive and monotonous for employees since the development of industrial automation. People more easily experience fatigue, both physical and mental [48]. However, because of low workload, detriment to health attributable to prolonged fatigue cannot be easily assessed.
The results of this survey of the employees of a Chinese automobile factory showed that although about half reported themselves to be in very good health, the majority had felt fatigue frequently in the past one or two months. Both engineers and workers had problems with fatigue, which was significantly correlated with work-related factors, especially the factors related to the working environment and monotony. The significance of the relationship between self-reported health condition and fatigue confirmed that people could ascertain their own physical condition exactly from their subjective feeling of their own bodies, which meant that the subjective measures for their fatigue status were effective and believable, and some authors have reported, “If the person tells you that he is loaded and effortful, then he is loaded and effortful whatever the behavioral and performances measures may show” [49]. In this study, engineers had better quality of sleep and greater satisfaction with the working conditions than workers did. Both of the scores of PSQI in engineers and workers were higher than the average score in healthy adults [42]. The mean score of engineers was closer to the previously documented in subjects without shift work disorder, while the mean score of workers was closer to the score in subjects with shift workdisorder [50].
The fatigue experienced by engineers was less affected by the length of the work day. This was probably because most of the engineers had more regular shift work- schedules and rest arrangements. They could balance work and rest on their own. However, the workers’ schedules were mostly arranged according to the production order.
The scores of fatigue between men and women did not show significant differences, but they did differ significantly between engineers and workers. The FACIT-F score was 42.6 (SD = 6.4) for engineers and 35.6 (SD = 6.3) for workers. Both these figures were worse than in the general population in the U.S., for which the score was 43.6 (SD = 9.4) [51]. The workers reported more fatigue than engineers.
The indexes for predicting prolonged fatigue showed general fatigue to be more likely to emerge regularly and frequently over a long period for engineers than for workers. However, the physical fatigue of workers usually had a long duration. In this way, workers may be more likely to experience musculoskeletal disorders, and the engineers were more likely to develop multi-diseases syndrome, such as chronic fatigue syndrome.
In contrast to the predictions made here, the self-reported health problems of engineers were related to physical fatigue, but for workers they came mainly from mental fatigue. This is probably because doing the same job for a long time caused the employees to become skilled, then they would complete the tasks by a more effective method. That is, the workers could more easily deal with fatigue from physical work, and the engineers could easily deal with fatigue from mental work. The result was that people would be easily fatigued by tasks with which they were not familiar. Among work-related factors, working environments and monotony were more likely to induce general fatigue in engineers than in workers. Among workers, monotony was more likely to induce physical fatigue, working environment was more likely induce mental fatigue, and length of the work day was more likely to induce general fatigue. In this way, the improvement of working environment and monotony might help alleviate fatigue in both engineers and workers. The combination of appropriate work day and break schedules would be more effective in alleviating workers’ fatigue.
The results of this study need to be viewed with regard to several limitations. First, the work-related fatigue is prevalent in repetitive industrial work [48], in this study we only surveyed the fatigue and fatigue-related factors among engineers and workers in an automobile factory, further investigations should be conducted among more samples from different industries. Second, although we selected some fatigue-related factors, they were not insufficient, more influential factors should be considered in further research, for instance, shift work, which is highly associated with work-related fatigue [52, 53].
Conclusion
The prevalence of work-related fatigue was high among participating employees from this automobile factory, and workers felt more fatigue than engineers. The fatigue observed here was significantly correlated with work-related factors, especially working environment and monotony. For workers, length of the work day also significantly affected their fatigue. Some improvements in work-related factors in this automobile factory should be considered. Prolonged fatigue status in the employees might also induce occupational disease, such as musculoskeletal disorders and chronic fatigue syndrome. To assess people’s working conditions, WCQ, a new questionnaire, was developed and tested here. It showed acceptable reliability and validity. Results also showed fatigue to be more severe when people performed tasks with which they were not familiar, so some targeted training might help prevent fatigue.
Conflict of interest
The authors declare that they have no conflicts of interest. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee. Informed consent was obtained from all individual participants included in the study.