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Article

Structural Equation Modeling of Musculoskeletal Pains, Work–Family Conflict, and Sleep-Related Problems on Well-Being of Food Manufacturing Workers

by
Jun Won Kim
and
Byung Yong Jeong
*
Industrial and Systems Engineering, Hansung University, Seoul 02876, Republic of Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(17), 8093; https://doi.org/10.3390/app14178093
Submission received: 12 August 2024 / Revised: 28 August 2024 / Accepted: 7 September 2024 / Published: 9 September 2024
(This article belongs to the Section Applied Biosciences and Bioengineering)
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Abstract

:
The objective of this study is to investigate the causal relationships between musculoskeletal pains, work–family conflict, sleep-related problems, and the well-being of food manufacturing workers using structural equation modeling. This study analyzed 523 food manufacturing workers extracted from the Sixth Korea Working Conditions Survey. We formulated six hypotheses based on literature reviews and examined the structural causal relationship between work–family conflict, musculoskeletal pains, sleep-related problems, and well-being. According to the results of structural equation modeling, work–family conflict has a significant impact on musculoskeletal pains (standardized path coefficient of 0.113). Furthermore, both musculoskeletal pains (standardized path coefficient of 0.350) and work–family conflict (standardized path coefficient of 0.212) have been found to affect sleep-related problems. It has also been established that musculoskeletal pains have a direct influence on well-being (standardized path coefficient of 0.115). The association and structural causality between musculoskeletal pain and psychological factors in food manufacturing workers can be used for customized measures to improve the well-being of food manufacturing workers. This study is also meaningful in that musculoskeletal pain and psychological factors should be managed in an integrated manner.

1. Introduction

1.1. Purpose of Study

Food manufacturing involves processing, converting, preparing, preserving, and packaging plant or animal-based raw materials for consumption [1]. Food manufacturing workers produce a variety of foods, including processed meat, sausages, ice cream, confectioneries, bread, rice cakes, and pickled foods [2,3]. The nature of work in food manufacturing often involves shift work, night work, and long hours [4,5,6], which can lead to work–family conflict [7]. Food manufacturing workers often experience musculoskeletal pains due to repetitive and forceful movements, as well as awkward postures [1]. Work–family conflict can lead to various health and productivity issues, such as musculoskeletal pains, decreased work quality and output, and sleep-related problems [8,9,10,11]. Sleep-related problems encompass various symptoms, such as disruption of regular sleep patterns, difficulty falling asleep, apnea, nightmares, and sleepwalking [12]. These problems significantly impact workers’ well-being [13]. Musculoskeletal pains and work–family conflict are also known to be significant factors affecting the well-being of workers [14,15]. The well-being of employees has a significant impact on their individual performance [16] as well as the productivity of the organization [17,18].
Research on the health issues faced by food manufacturing workers is limited despite their experience with musculoskeletal pains, sleep-related problems, work–family conflict, and well-being. Furthermore, there is a lack of research analyzing the causal relationships between work–family conflict, musculoskeletal pains, sleep-related problems, and well-being. This study aims to identify the causal relationships between musculoskeletal pains, work–family conflict, sleep-related problems, and the well-being of food manufacturing workers using a structural equation model (SEM).

1.2. Theoretical Background

1.2.1. Work–Family Conflict

Work–family conflict refers to the degree to which workers are dissatisfied with their work and family roles, including time-sharing, participation, and satisfaction [19]. Workers in the food manufacturing industry put in an average of 8.6 h daily [20], and long working hours may lead to work–family conflict due to a lack of time sharing with family [21]. Work–family conflict is known to hurt workers’ health and productivity [22].

1.2.2. Musculoskeletal Pains

Musculoskeletal diseases refer to health disorders that appear in the body due to damage to tissues such as muscles, nerves, tendons, ligaments, and joints due to factors such as excessive use of force, repetitive movements, inappropriate working posture, vibration, and temperature [23]. Workers in food manufacturing have a high rate of musculoskeletal pain complaints [24,25,26,27,28,29]. It is known that the level of musculoskeletal pain increases with higher work–family conflict [30,31,32]. However, there was a lack of research analyzing the relationship between work–family conflict and musculoskeletal pains in food production workers. Therefore, we established the following hypothesis.
Hypothesis 1 (H1).
Work–family conflict will positively affect musculoskeletal pains.

1.2.3. Sleep-Related Problems

Sleep-related problems include insomnia, narcolepsy, and sleep apnea [33]. The work patterns of workers in the food industry consist of night and shift work [5], which disrupts biological rhythms and increases the risk of sleep-related problems [34,35]. As work–family conflict becomes more serious, it negatively impacts sleep time and quality [36,37]. Additionally, musculoskeletal pains can impact sleep-related problems [38,39,40,41,42,43]. Therefore, we have formulated the following hypotheses.
Hypothesis 2 (H2).
Work–family conflict will positively affect sleep-related problems.
Hypothesis 3 (H3).
Musculoskeletal pains will positively affect sleep-related problems.

1.2.4. Well-Being

Well-being refers to a positive state experienced by individuals and society [44]. It means judging life positively and feeling good [45]. A significant factor affecting well-being is sleep-related problems [46,47,48], and having persistent sleep problems can have a negative impact on your physical and emotional well-being [49]. Work–family conflict has a significant impact on well-being [50] and can reduce the well-being of workers [51]. Meanwhile, musculoskeletal pain is evaluated as the most important health aspect related to well-being and enjoyment of life [52]. Other than its impact on physical health, it also has a negative effect on an individual’s emotional and social well-being [14,53]. Therefore, we have formulated the following hypotheses.
Hypothesis 4 (H4).
Work–family conflict will affect well-being.
Hypothesis 5 (H5).
Musculoskeletal pains will affect well-being.
Hypothesis 6 (H6).
Sleep-related problems will affect well-being.

1.2.5. Hypothesis Testing and SEM

This study uses the SEM to analyze the structural causality between musculoskeletal pains, work–family conflict, and sleep-related problems affecting well-being. Studies using SEM include the modeling of job dissatisfaction among truck drivers [11], satisfaction levels of office workers [54], perceptions of safety among waste and recycling collectors [55], work engagement of commercial motor vehicle drivers [56], and musculoskeletal pain among older female farmers [57]. In this study, we aim to comprehensively test structural causality using SEM instead of independently testing each of the six hypotheses derived from the literature review.

2. Methods

2.1. Data Collection and Subjects

This study analyzed the Sixth Korea Working Conditions Survey (KWCS) data, which surveyed 50,538 workers [58]. Out of the total data, 759 respondents corresponding to the food manufacturing industry were extracted based on the Korean Standard Industrial Classification (KSIC) [3]. Production workers were extracted based on the Korean Standard Occupational Classification [59], and respondents with missing values were excluded. Finally, 523 food manufacturing production workers were selected as the research subjects.

2.2. Research Variables

This study’s research variables were chosen from KWCS questionnaire items [58]. The variables for this study were work–family conflict, musculoskeletal pain, sleep-related problems, and well-being. Table 1 shows the variables and measurement variables of this study. In Table 1, work–family conflict is measured using five items (worry, tired, family, concentration, and responsibility) in response to the question, ‘How often have you experienced the following situations in the past year?’ Musculoskeletal pain comprised responses to the question, ‘During the past year, have you had any health problems such as backache, upper extremity pain, or lower extremity pain?’ Sleep-related problems were measured by three items (difficulty falling asleep, waking up repeatedly, and feeling exhausted or fatigued) in response to the question, ‘How often have you experienced the following sleep problems in the past year?’ Well-being was evaluated using the Well-being Index, developed by the World Health Organization (WHO-5) [60]. The well-being score is based on five items: feeling good, rested, active, energetic, and interested. Respondents answer the question ‘How often have you experienced these feelings over the past two weeks?’ The scales for the items of each variable are shown in Table 1. The well-being score of Table 1 is interpreted so that a higher score indicates a more negative state of well-being. So, if any factors such as work–family conflict, sleep-related problems, and musculoskeletal pain are positively related to well-being, it means that they hurt one’s well-being.

2.3. Data Analysis and Structural Equation Modeling

Based on a literature survey, this study developed six hypotheses. The study uses a SEM depicted in Figure 1 to examine the structural causal relationship among work–family conflict, musculoskeletal pain, sleep-related problems, and well-being in food manufacturing production workers. In other words, this study seeks to determine whether work–family conflict affects musculoskeletal pain in food manufacturing production workers. Additionally, it aims to examine whether work–family conflict and musculoskeletal pain have an effect on sleep-related problems. Ultimately, the study intends to establish if there is a cause-and-effect relationship between work–family conflict, musculoskeletal pain, sleep-related problems, and well-being.

2.4. Reliability Analysis and SEM Fit Test

Reliability analysis was conducted using Cronbach’s Alpha values to measure the internal consistency of work–family conflict, musculoskeletal pain, sleep-related problems, and well-being variables. Additionally, a factor analysis was carried out to assess the validity of the construct.
In this study, SEM was verified using the model fit test and composite reliability analysis. The model’s fit was confirmed through goodness of fit indices, such as χ2, p-value, goodness-of-fit-index (GFI), root mean square residual (RMR), root mean square error of approximation (RMSEA), normed fit index (NFI), relative fit index (RFI), incremental fit index (IFI), comparative fit index (CFI), Tucker–Lewis index (TLI). RMR and RMSEA are considered good if they are below 0.05 [61], and acceptable if they are below 0.08 [62,63]. GFI, NFI, RFI, IFI, CFI, and TLI are considered good if they are 0.9 or higher and acceptable if they are higher than 0.85 [62,64,65,66]. The convergent validity of the model was analyzed using the average variance extracted (AVE), composite reliability (CR), and correlation coefficients between variables. AVE should be greater than 0.5 and CR should be greater than 0.7 to be suitable [67]. The statistical analysis of the data was carried out using SPSS version 21.0 and AMOS 22.0.

3. Results

3.1. Reliability Analysis

Table 2 shows the final results of the reliability analysis, which evaluated the internal consistency of the subjective survey item variables. For the musculoskeletal pain, sleep-related problems, and well-being variables, no items were removed. Cronbach’s Alpha value was above 0.7, indicating adequate internal consistency reliability.

3.2. Exploratory Factor Analysis

Table 3 shows the final results of factor analysis of subjective survey variables. According to a result of factor analysis of the survey questions using the Varimax rotation method, it was found to be composed of four component factors: (1) well-being, (2) work–family conflict, (3) sleep-related problems, and (4) musculoskeletal pains. Additionally, the Bartlett test result was significant (p < 0.001), and the Kaiser–Meyer–Olkin (KMO) test also produced a significant result (0.817 > criteria = 0.60). The reliability analysis and factor analysis results indicate that all research variables and component factors have satisfactory reliability and construct validity.

3.3. Results of Model Fit and Convergent Validity Analysis

Table 4 presents the results of the model fit tests. The results of the model fit tests were χ2 = 233.280 (p < 0.001), GFI = 0.940 (good fit: 0.90 ≤ GFI), RMR = 0.045 (good fit: RMR < 0.05), RMSEA = 0.059 (acceptable fit: 0.05 < RMSEA ≤ 0.08), NFI = 0.948 (good fit: 0.90 < NFI), RFI = 0.934 (good fit: 0.90 < RFI), IFI = 0.966 (good fit: 0.90 < IFI), CFI = 0.966 (good fit: 0.90 < CFI), and TLI = 0.957 (good fit: 0.90 < TLI). Therefore, SEM fit was evaluated as acceptable.
The results of the convergent validity of the model can be found in Table 5. In Table 5, the CR value is greater than the acceptable criteria (0.7). The AVE values are greater than 0.5, and the correlations between the variables are less than the AVE values. The AVE values are also greater than the squared value of the correlation coefficient. These results demonstrate that the validity of the model has been achieved.

3.4. Hypothesis Testing of the SEM

The outcomes of the hypothesis testing for the proposed relationships are demonstrated in Table 6. Work–family conflict significantly impacted musculoskeletal pains (p = 0.032). Moreover, musculoskeletal pains had a significant effect on sleep-related problems (p < 0.001), and work–family conflict also had a significant impact on sleep-related problems (p < 0.001). Therefore, it can be concluded that H1, H2, and H3 are statistically adopted. However, H4 (H4: sleep-related problems will affect well-being, p = 0.191) and H5 (H5: work–family conflict will affect well-being, p = 0.248) were not supported. On the contrary, musculoskeletal pains impacted well-being (p = 0.045). Thus, H6 is statistically supported.

3.5. Results of Structural Equation Modelling

Figure 2 shows the SEM that was ultimately adopted in this study. Work–family conflict was found to affect musculoskeletal pain (standardized path coefficient = 0.113). This means that the greater the work–family conflict, the greater the complaints of musculoskeletal pain. The influential variables of work–family conflicts are concentration (0.933) and responsibility (0.907).
Work–family conflict was also found to have an effect on sleep-related problems (standardized path coefficient = 0.212). This indicates that the greater the work–family conflict, the greater the sleep-related problems. Additionally, musculoskeletal pain impacted sleep-related problems (standardized path coefficient = 0.350). This can be interpreted as the more musculoskeletal pain complaints, the greater the sleep-related problems. The influential variables of musculoskeletal pain were upper extremity pain (0.760) and back pain (0.715). Sleep-related problems were more affected by musculoskeletal pain (0.350) than work–family conflict (0.212). The influential variables of sleep-related problems were waking up repeatedly (0.902), difficulty falling asleep (0.816), and exhaustion/fatigue (0.801).
Musculoskeletal pain was also found to affect well-being (standardized path coefficient = 0.115). This can be interpreted as the more a worker complains of musculoskeletal pain, the more it negatively affects their well-being. On the other hand, sleep-related and work–family conflict had no statistically significant effect on well-being. The influential variables of well-being were good spirit (0.893), active (0.856), vitality (0.807), relaxation (0.806), and interest (0.784).

4. Discussion

This study used structural equations to analyze the relationship between work–family conflict, musculoskeletal pains, sleep-related problems, and well-being among workers in the food manufacturing industry. The research results show that work–family conflict has an impact on musculoskeletal pain. This finding is consistent with research indicating that work–family conflict can lead to musculoskeletal symptoms such as neck and back pain [8,30,31,32].
Work–family conflict has also been shown to affect sleep-related problems. This is consistent with the results that the greater the work–family conflict, the higher the risk of waking up multiple times at night, the difficulty in falling asleep again, as well as the likelihood of sleep-related problems such as waking up tired [68,69,70]. The results are consistent with the findings that construction workers and IT workers experience sleep-related problems due to work–family conflict [71,72]. As work hours increase, work–family conflict may worsen [73,74]. Thus, managing work hours of food manufacturing workers can reduce work–family conflict. Musculoskeletal pain has also been shown to contribute to sleep-related problems. This is in line with research indicating that musculoskeletal pain can have a negative impact on both the quantity and quality of sleep, resulting in difficulty falling asleep and conditions such as insomnia, narcolepsy, and sleep apnea [9,10,40,41,42,43]. In addition, the sleep quality of workers in hospitals and electronic component manufacturing plants was found to be linked to musculoskeletal pain [38,75].
Musculoskeletal pain has been shown to have a negative impact on well-being. This was consistent with the finding that the group complaining of musculoskeletal pain had lower overall psychological well-being than the non-complainers [76,77] and that musculoskeletal pain had a negative effect on psychological well-being [78]. These results suggest that preventing musculoskeletal pain is important to improve the well-being of food manufacturing workers. Food manufacturing workers are prone to musculoskeletal pain because they use hand tools, handle heavy objects, and perform repetitive tasks [79,80]. Physical therapy for patients with neck, shoulder, or back pain can improve not only pain but also psychological well-being [81]. Appropriate education is also important to understand the causes and prevention of musculoskeletal pain [1,81].
This study presents effective measures to manage food manufacturing workers’ well-being, sleep problems, musculoskeletal pain, and work–family conflict. First, musculoskeletal pain is the factor that most directly affects well-being, suggesting that managing workers with musculoskeletal pain is paramount. In particular, it is necessary to manage food manufacturing workers’ upper limb, back, and lower limb pain. Second, the sleep-related problems of food manufacturing workers were influenced by musculoskeletal pain and work–family conflict, and it was found that musculoskeletal pain was particularly affected among the two. Third, because the presence of musculoskeletal pain is influenced by work–family conflict, this suggests that efforts are needed to reduce work–family conflict factors. In particular, efforts are needed to improve major factors in work–family conflict, such as “not giving time to work because of family” and “difficult to concentrate on work because of family”. Lastly, integrated management using structural relationships is needed for well-being, sleep problems, musculoskeletal pain, and work–family conflict.
This study has some limitations. First, this study did not target the entire food manufacturing industry, so caution is needed in interpretation. Second, this survey identified psychological factors based on subjective questionnaires but did not include psychological factors such as job stress, social support, and organizational satisfaction, interpreted as factors affecting well-being. Therefore, future research that comprehensively includes this is expected. Lastly, since this study did not identify hazard factors affecting musculoskeletal pain, sleep problems, and work–family conflict among food manufacturing workers, future research on factors affecting these factors is expected.

5. Conclusions

The strength of this study is that it revealed the association and structural causal relationship between musculoskeletal pains and psychological factors in the food manufacturing industry. The food manufacturing workers’ musculoskeletal pains were related to work–family conflict, and sleep problems were related to work–family conflict and musculoskeletal pains. In addition, well-being was closely related to musculoskeletal pains. These relationships suggest customized measures to improve the well-being of food manufacturing workers. This study is also meaningful in that musculoskeletal pain and psychological factors should be managed in an integrated manner.

Author Contributions

Conceptualization, J.W.K. and B.Y.J.; methodology, J.W.K. and B.Y.J.; data collection and analysis, J.W.K.; data curation, J.W.K. and B.Y.J.; writing—original draft preparation, J.W.K. and B.Y.J.; writing—review and editing, J.W.K. and B.Y.J.; supervision, B.Y.J.; funding acquisition, B.Y.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by Hansung University.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Publicly available datasets were analyzed in this study. These data can be found here: https://www.kosha.or.kr/eoshri/resources/KWCSDownload.do, accessed on 13 August 2024.

Acknowledgments

The authors are grateful to the Occupational Safety and Health Research Institute (OSHRI) and the Korea Occupational Safety and Health Agency (KOSHA) for providing the raw data from the KWCS.

Conflicts of Interest

The authors declare no conflicts of interest.

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Applsci 14 08093 g001
Figure 1. Conceptual structural equation model (SEM) of this study. Rectangle, measurement variable; ellipse, latent variable; Di, disturbance or residual; ei, measurement error.
Figure 1. Conceptual structural equation model (SEM) of this study. Rectangle, measurement variable; ellipse, latent variable; Di, disturbance or residual; ei, measurement error.
Applsci 14 08093 g001
Applsci 14 08093 g002
Figure 2. Final SEM of this study. Rectangle represents measurement variable, and ellipse represents latent variable. Di: disturbance or residual; ei: measurement error.
Figure 2. Final SEM of this study. Rectangle represents measurement variable, and ellipse represents latent variable. Di: disturbance or residual; ei: measurement error.
Applsci 14 08093 g002
Table 1. Latent variables and measurement variables of this study.
Table 1. Latent variables and measurement variables of this study.
Latent VariableMeasurement VariablesVariable AbbreviationDescription
Work–family conflictWorry about work when not workingWorry1. Never~
5. Always
Too tired after work to do household workTired
Job prevents giving time to familyFamily
Hard to concentrate on job because of familyConcentration
Family prevents giving time to jobResponsibility
Musculoskeletal painsBackacheBackache0. No, 1. Yes
Muscular pains in upper limbsUpper limb pain
Muscular pains in lower limbsLower limb pain
Sleep-related problemsDifficulty falling asleepDifficulty falling asleep1. Never~
5. Daily
Waking up repeatedly during the sleepWaking up repeatedly
Waking up with a feeling of exhaustion and fatigueExhaustion/fatigue
Well-beingI have felt cheerful and in good spiritsCheerful0. Always~
5. Never
I have felt calm and relaxedRelaxed
I have felt active and vigorousActive
I woke up feeling fresh and restedRested
My daily life has been filled with things that interest meInteresting
Table 2. Results of reliability analysis of variables using Cronbach’s Alpha.
Table 2. Results of reliability analysis of variables using Cronbach’s Alpha.
Latent VariableInitial ItemsRemoved Question ItemFinal ItemsCronbach’s Alpha
Work–family conflict5Worry40.847
Musculoskeletal pains3 30.758
Sleep-related problems3 30.875
Well-being5 50.916
Table 3. Results of exploratory factor analysis after variable removal through reliability analysis.
Table 3. Results of exploratory factor analysis after variable removal through reliability analysis.
FactorMeasurement VariableComponent
1234
Well-beingCheerful0.9040.0570.0230.038
Active0.8840.0700.0010.019
Relaxed0.8490.0580.028−0.032
Rested0.8410.0820.1220.130
Interesting0.837−0.0890.0390.069
Work–family conflictConcentration0.0070.8940.078−0.031
Responsibility0.0540.8830.072−0.050
Family0.0310.7810.0990.140
Tired0.0620.7380.1960.207
Sleep-related problemsWaking up repeatedly0.0520.1120.8980.141
Difficulty falling asleep0.0680.1120.8800.076
Exhaustion/fatigue0.0440.1820.8380.195
Musculoskeletal painsUpper limb pain0.0870.0310.1280.824
Backache0.0370.1220.1140.800
Lower limb pain0.0310.0460.1180.787
% of Variance28.89921.21113.8459.962
Cumulative (%)73.917
Kaiser–Meyer–Olkin test0.817
Bartlett’s testp < 0.001
Table 4. Results of model fit test.
Table 4. Results of model fit test.
Goodness of Fit IndexGood FitAcceptable FitStructural Model
χ2 233.280
df 83
χ2/df<22.0~5.02.811
p-value<0.0010.050<0.001
RMR<0.050.05~0.080.045
RMSEA<0.050.05~0.080.059
GFI>0.900.85~0.900.940
NFI>0.900.85~0.900.948
RFI>0.900.85~0.900.934
IFI>0.900.85~0.900.966
CFI>0.900.85~0.900.966
TLI>0.900.85~0.900.957
Table 5. Convergent validity and correlations with variables.
Table 5. Convergent validity and correlations with variables.
HypothesisMusculoskeletal PainsWork–Family ConflictSleep-Related ProblemsAVECR
Musculoskeletal pains 0.8320.937
Work–family conflict0.125 0.6400.872
Sleep-related problems0.3740.261 0.7840.916
Well-being0.1480.0920.1290.6070.885
AVE = average variance extracted; CR = composite reliability.
Table 6. Results of hypothesis testing of the proposed relationships.
Table 6. Results of hypothesis testing of the proposed relationships.
HypothesisPathsStandardized
Coefficient (λ)		Critical Ratiop-ValueResult
H1Work–family conflict
→ Musculoskeletal pains		0.0682.1390.032 *Supported
H2Musculoskeletal pains
→ Sleep-related problems		0.6356.460<0.001 *Supported
H3Work–family conflict
→ Sleep-related problems		0.2344.420<0.001 *Supported
H4Sleep-related problems
→ Well-being		0.1241.3080.191Not supported
H5Work–family conflict
→ Well-being		0.1081.1560.248Not supported
H6Musculoskeletal pains
→ Well-being		0.3632.0070.045*Supported
* Significant difference at 0.05.
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Kim, J.W.; Jeong, B.Y. Structural Equation Modeling of Musculoskeletal Pains, Work–Family Conflict, and Sleep-Related Problems on Well-Being of Food Manufacturing Workers. Appl. Sci. 2024, 14, 8093. https://doi.org/10.3390/app14178093

AMA Style

Kim JW, Jeong BY. Structural Equation Modeling of Musculoskeletal Pains, Work–Family Conflict, and Sleep-Related Problems on Well-Being of Food Manufacturing Workers. Applied Sciences. 2024; 14(17):8093. https://doi.org/10.3390/app14178093

Chicago/Turabian Style

Kim, Jun Won, and Byung Yong Jeong. 2024. "Structural Equation Modeling of Musculoskeletal Pains, Work–Family Conflict, and Sleep-Related Problems on Well-Being of Food Manufacturing Workers" Applied Sciences 14, no. 17: 8093. https://doi.org/10.3390/app14178093

APA Style

Kim, J. W., & Jeong, B. Y. (2024). Structural Equation Modeling of Musculoskeletal Pains, Work–Family Conflict, and Sleep-Related Problems on Well-Being of Food Manufacturing Workers. Applied Sciences, 14(17), 8093. https://doi.org/10.3390/app14178093

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