Relationship between Negative Work Situation, Work-Family Conﬂict, Sleep-Related Problems, and Job Dissatisfaction in the Truck Drivers

: Understanding the relationship between psychological factors of truck drivers is very important for accident prevention plans. This study investigates whether the negative work situation or work-family conﬂict positively a ﬀ ects sleep-related problems and whether sleep-related problems positively a ﬀ ect job dissatisfaction. The relationship was veriﬁed by structural equation modeling. The analysis was conducted with 184 truck drivers who drive daily from the 5th Korea Working Conditions Survey (KWCS) data. The structural equation modeling results found that work-family conﬂict (standardized path coe ﬃ cient = 0.274) and negative work situation (standardized path coe ﬃ cient = 0.203) had signiﬁcantly a ﬀ ected sleep-related problems. Also, the sleep-related problems were more a ﬀ ected by the work-family conﬂict level than the negative work situation level. Sleep-related problems were found to correlate with job dissatisfaction (standardized path coe ﬃ cient = 0.336). The relationship between negative work situation and work-family conﬂict on sleep-related problems and job dissatisfaction will help establish preventive policies for truck drivers’ safety and health. D.S.S. and B.Y.J.; methodology, D.S.S. and B.Y.J.; data collection & analysis, D.S.S.; resources, D.S.S. and B.Y.J.; data curation, D.S.S.; writing—original draft preparation, D.S.S. and B.Y.J.; writing—review and editing, D.S.S. and B.Y.J.; supervision, D.S.S.; funding acquisition, D.S.S.


Truck Drivers and Purpose of Study
Truck drivers who transport cargo to a local region or long-haul area play a role in the e-commerce and logistics industries [1]. In Korea Standard Classification of Occupations [2], truck and special truck drivers are classified into freight-vehicle drivers and special-purpose-vehicle drivers. Freight-vehicle is defined as a truck whose loaded weight is larger than the total weight of passengers inside, and a special-purpose-vehicle is a vehicle that is adequately designed to perform particular tasks [3]. In this study, truck drivers include freight-vehicle drivers and special-purpose-vehicle drivers. In 2018, there were 1,235,045 workers at 383,737 establishments in the freight trucking industry of South Korea [4].
Truck drivers' tasks include checking the transport records and delivering the vehicle to its destinations [1]. Truck drivers are treated as self-employed in South Korea [1]. Some self-employed truck drivers buy or lease trucks and go into business for themselves [1]. Truck drivers who are self-employed can control the number of workdays and their schedules. Truck drivers can maintain their income by long working hours because of intensified competition [5]. Self-employed truck drivers who purchase cars as installments are subject to economic pressure due to car payments and tend to increase workdays to increase their monthly income. They often have to drive until the late hours of the night, and they may experience irregular and insufficient meals [5].

Work Situation
The work situation is the social relationships that workers enter into their workplace [26]. It is related to the work environment, employment conditions, and employee's satisfaction [27]. It also includes individual rights and professional development opportunities within the company [28]. The truck driver's working conditions still are not good, and negative work situations are common [1,5]. In this study, negative work situations mean unfortunate or hostile social relationships that workers experience in their workplace. The negative work situation in the workplace saps energy and diverts attention from productivity and performance [20]. It can also lead to poor mental health outcomes, especially sleep-related problems.
This research created the following hypotheses: Hypothesis 1 (H1): Negative work situations positively affect sleep-related problems.

Work-Family Conflict
Extended driving hours and irregular schedules can reduce the likelihood of family spending and lead to work-family conflict. Work-family conflict is the degree to which workers are not satisfied with the role of work and family: time-sharing, involvement, and satisfaction with work and family [16,17]. One primary reason for the work-family conflict is the lack of time-sharing due to extended driving hours [17]. Work-life conflict, social isolation, or unfortunate work situations can intrude into workers' private lives, leading to sleep-related problems [17,18].
As explained in the literature above, this study hypothesized: Hypothesis 2 (H2): Work-family conflicts positively affect sleep-related problems.

Job Satisfaction
Job satisfaction can be defined as the subjective interpretation of individual opinion based on the extent of fulfilling their requirements at work and in work situations, relationships, or activities related to it [26,27]. It also refers to a personal attitude, such as the overall impression, feeling, and evaluation that an individual has about the job. In this study, job dissatisfaction means the negative attitude or evaluation that workers have about the job. Job dissatisfaction can lead to negative outcomes [29]. Truck drivers suffer from sleep-related problems, and job dissatisfaction is common [13,19,21,25]. Sleep-related problems can cause a truck driver's job dissatisfaction. Thus, this research created the following hypotheses:

Data Collection
This study used data and questionnaires from the 5th Korea Working Conditions Survey (KWCS) in 2017. KWCS is a national survey to investigate workers' working conditions and risk factors by industry [30]. The questionnaire used in this study is identical to that of the 6th European Working Conditions Survey (EWCS) [31]. The raw data of the KWCS was received from the Institute for Occupational Safety and Health [30].
In the 5th KWCS, 50,205 workers participated in proportion to each region's population in South Korea. Among them, drivers in the freight trucking industry were selected as this study's subjects. A total of 184 professional truck drivers were extracted as the final data. All of them were male, with 11.4% of those ≥ 60 years, and 38.6% of those in their 50s. The mean of driver's age was 54.9 years, with a standard deviation of 9.40.

Research Variables
The research variables consisted of latent variables for a negative work situation, work-family conflict, sleep-related problems, and job dissatisfaction. Table 1 shows the latent variables and measurement variables for each latent variable. As shown in Table 1, all measurement variables were scored to the Likert scaling from 1 to 5.
Negative work situation was based on the Q49 questions of the 2017 KWCS questionnaire (same as Q61 questions of the 2015 EWCS questionnaire) [31]. Some of the Q49 measurement variables in the KWCS questionnaire were removed through prior reliability analysis. The measurement variables for the negative work situations in Table 1 represent the results after prior removal.
Work-family conflict was represented by the Q38 questions of the 2017 KWCS questionnaire (same as Q45 questions of the 2015 EWCS questionnaire). As shown in Table 1, these questions have five measurement variables on work-family conflict [31].
Sleep-related problems were represented by the Q63 questions of the 2017 KWCS questionnaire (same as Q79 questions of the 2015 EWCS questionnaire). As shown in Table 1, these questions have three measurement variables on sleep-related problems [18].
Job dissatisfaction was based on the Q71 questions of the 2017 KWCS questionnaire (same as Q90 questions of the 2015 EWCS questionnaire). As shown in Table 1, it is the same as Warr et al.'s job dissatisfaction index [32].

Data Analysis and Structural Equation Model
This study proposed hypotheses based on the literature review. The hypotheses are as follows: This study merged two relationships to create a more robust model. Sleep-related problems were a dependent variable and an explanatory variable in the model. The relationship was verified by structural equation modeling (SEM). SEM has the advantage of estimating this kind of interdependence of several variables that reflect measurement errors. Figure 1 shows the initial structural model. In Figure 1, ellipse means latent variable, and a rectangle is the measurement variable. Di is a disturbance or residual, and ei is measurement error.
In the structural equation model, negative work situation, which is a latent variable, is measured by 6 questionnaire items, work-family conflict by 5 questionnaire questions, sleep-related problems by 3 questionnaire questions, and job dissatisfaction by 6 questionnaire questions.
AMOS 18 and SPSS version 18.0 were used as analytical tools. The internal consistency of measured variables was performed by reliability analysis. Some measurement variables were eliminated by the standardized Cronbach's alpha. The convergent validity was confirmed through factor analysis. Path analysis was then performed to evaluate the proposed hypotheses.  Table 2 displays the final results of reliability analysis to ensure the internal consistency of the measurement variables. As shown in Table 2, two measurement variables in negative work situation and two measurement variables in job dissatisfaction were removed by Cronbach's alpha. The final result of reliability analysis yields a Cronbach's α value of 0.821, and it is very satisfactory.

Exploratory Factor Analysis
Factor analysis was useful for refining measures and evaluating construct validity. In Bartlett's test and Kaiser-Meyer-Olkin (KMO) test results, Bartlett's test was significant (p < 0.001), and the KMO was above 0.60 (0.774). Factor analytical results, shown in Table 3, revealed that the factors could be classified into four dimensions: negative work situation, work-family conflict, sleep-related problems, and job dissatisfaction. From Tables 2 and 3, research variables and factors showed acceptable reliability and construct validity.  Table 2 displays the final results of reliability analysis to ensure the internal consistency of the measurement variables. As shown in Table 2, two measurement variables in negative work situation and two measurement variables in job dissatisfaction were removed by Cronbach's alpha. The final result of reliability analysis yields a Cronbach's α value of 0.821, and it is very satisfactory.

Exploratory Factor Analysis
Factor analysis was useful for refining measures and evaluating construct validity. In Bartlett's test and Kaiser-Meyer-Olkin (KMO) test results, Bartlett's test was significant (p < 0.001), and the KMO was above 0.60 (0.774). Factor analytical results, shown in Table 3, revealed that the factors could be classified into four dimensions: negative work situation, work-family conflict, sleep-related problems, and job dissatisfaction. From Tables 2 and 3, research variables and factors showed acceptable reliability and construct validity.

Structural Model Assessment
A chi-square test value usually determines the model fit, and other indices have been used for the assessment. The goodness of fit (GOF) was evaluated and compared with the suggested criteria shown in Table 4. The goodness of fit indices in Table 4 represented an acceptable fit of the model (χ 2 = 202.898, p < 0.001; NFI = 0.821; CFI = 0.897; GFI = 0.878; TLI = 0.874; RMSEA = 0.076).

Convergent Validity
The convergent validity was confirmed by average variance extracted (AVE) and composite reliability (CR). In Table 5, CR values were between 0.784 and 0.874 (acceptable criteria: > 0.70), so these results show strong composite reliability. The AVE values were also greater than correlations between variables, so the results supported convergent validity.  Figure 2 represents the direction of the correlation between latent variables. Figure 2 shows that the proposed relationships have the same directions, with relationships shown in Figure 2. The results supported the nomological validity.   Figure 2 represents the direction of the correlation between latent variables. Figure 2 shows that the proposed relationships have the same directions, with relationships shown in Figure 2. The results supported the nomological validity.

Hypothesis Testing of the Structural Model
The structural model was evaluated to validate the hypothesized relationships. Table 6 represents the results of hypothesis testing for the proposed relationships among the constructs.
In Table 6, negative work situation and work-family conflict were found to have significantly positive effects on sleep-related problems. Thus, H1 and H2 were statistically validated. Similarly, sleep-related problems significantly influenced job satisfaction. H3, therefore, was statistically supported.

Hypothesis Testing of the Structural Model
The structural model was evaluated to validate the hypothesized relationships. Table 6 represents the results of hypothesis testing for the proposed relationships among the constructs.
In Table 6, negative work situation and work-family conflict were found to have significantly positive effects on sleep-related problems. Thus, H1 and H2 were statistically validated. Similarly, sleep-related problems significantly influenced job satisfaction. H3, therefore, was statistically supported.

Effect of Work Situation and Work-Life Balance on Sleep-Related Problems and Job Satisfaction
As shown in Figure 3, negative work situations positively affected sleep-related problems (standardized path coefficient = 0.203). It can be interpreted that the higher the level of the negative work situation, the more significant influence on sleep-related problems. Among the measurement variables for a negative work situation, 'feeling well' (0.752) and 'enough time' (0.666) were found to be the influential variables.
The work-family conflict also had a significant impact on sleep-related problems (standardized path coefficient = 0.274). In other words, a higher work-family conflict level led to a higher level of sleep-related problems. Among the measurement variables for work-family conflict, 'family' (0.825) and 'tired' (0.721) were found to be the influential variables.
Also, sleep-related problems were more affected by the level of work-family conflict (0.274) than the negative work situation (0.203). Among the measurement variables for sleep-related problems, 'waking up repeatedly' (0.851) and 'difficulty fall asleep' (0.845) were the influential variables.
On the other hand, the sleep-related problems (standardized path coefficient = 0.336) affected job dissatisfaction. That is, a higher level of sleep-related problems led to a higher level of job dissatisfaction. Among the measurement variables for job satisfaction, 'enthusiastic' (0.792) and 'energy' (0.731) were the influential variables.

Effect of Work Situation and Work-Life Balance on Sleep-Related Problems and Job Satisfaction
As shown in Figure 3, negative work situations positively affected sleep-related problems (standardized path coefficient = 0.203). It can be interpreted that the higher the level of the negative work situation, the more significant influence on sleep-related problems. Among the measurement variables for a negative work situation, 'feeling well' (0.752) and 'enough time' (0.666) were found to be the influential variables.
The work-family conflict also had a significant impact on sleep-related problems (standardized path coefficient = 0.274). In other words, a higher work-family conflict level led to a higher level of sleep-related problems. Among the measurement variables for work-family conflict, 'family' (0.825) and 'tired' (0.721) were found to be the influential variables.
Also, sleep-related problems were more affected by the level of work-family conflict (0.274) than the negative work situation (0.203). Among the measurement variables for sleep-related problems, 'waking up repeatedly' (0.851) and 'difficulty fall asleep' (0.845) were the influential variables.
On the other hand, the sleep-related problems (standardized path coefficient = 0.336) affected job dissatisfaction. That is, a higher level of sleep-related problems led to a higher level of job dissatisfaction. Among the measurement variables for job satisfaction, 'enthusiastic' (0.792) and 'energy' (0.731) were the influential variables.

Discussion
Truck drivers are exposed to sleep-related problems and stress due to physical and mental fatigue [33]. Irregular shift schedules and extended driving hours are related to mental problems and adverse effects on health behaviors. Truck drivers are highly stressed by irregular working hours and shifts, leading to drowsy driving or dangerous driving situations. Truck drivers complain about not getting enough information and support for safety and health management. They work isolated from family and colleagues, so they often do not have access to health-related resources [34]. Furthermore, fatigue and sleep disturbances affect circadian rhythms and increase traffic crashes [25]. Therefore, driving schedule planning, work redesign, and health protection programs should be considered to prevent collisions [35].
Age-related declines in cognitive, perceptual, and motor capabilities negatively affect driving performance [36]. In South Korea, as the elderly population increases, the average age of truck drivers is rising. In this study, the proportion of respondents aged ≥60 years accounted for 50.0% by reflecting the truck drivers' population ratio. Traffic crashes caused by elderly truck drivers are also increasing [1,5]. Thus, an active policy for elderly truck drivers is required. The driver-centered approach to the work environment and conditions can improve the work situation for safety and health [37,38]. Universal safety and design concepts can be an opportunity to enhance the working environment of older drivers and promote economic participation in society through policy and design considerations for seniors [39,40].
Limiting driving time can reduce work-family conflict and drowsiness [41]. Measures to ensure the effectiveness of hours-of-service regulation and institutional aspects regarding working hours and break times can improve working conditions. For truck drivers, how to monitor and implement a safe driving strategy is essential. U.S. truck drivers are required to have electronic onboard monitoring to adhere to hours of service regulations [42].
Workplace health and wellness program is being recognized as potentially enhancing employee health, satisfaction, and productivity. Researchers recommend psychological counseling as a way to improve a driver's sleep-related problem. Workplace health promotion programs also emphasize changes in health behavior [43]. Comprehensive efforts on working condition improvements and workplace health programs are recommended to yield better driver health outcomes [23,44] because comprehensive efforts could increase effectiveness and participation [37].

Conclusions
This research examined the interrelationships between negative work situation, work-family conflict, sleep-related problems, and job dissatisfaction. Based on the literature survey, this study tested three hypotheses on the interrelationships between negative work situation, work-family conflict, sleep-related issues, and job dissatisfaction. The results of this study suggested that negative work situation and work-family conflict significantly influence sleep-related problems in truck drivers. Also, truck drivers' sleep-related problems significantly affect their job dissatisfaction. The results of this study can be used to establish preventive policies for truck drivers' safety and health.