Using the Job Burden-Capital Model of Occupational Stress to Predict Depression and Well-Being among Electronic Manufacturing Service Employees in China
Abstract
:1. Introduction
2. Experimental Section
2.1. Population and Investigation Process
2.2. Hypotheses and Construction of Job Burden-Capital Matching Model
2.2.1. Measurement Method of Each Model Dimension
2.2.2. Job Burden
2.2.3. Capital
2.2.4. Personality
2.2.5. Depression
2.2.6. Well-Being
2.2.7. Statistical Processing
2.3. Ethics Review and Approval
3. Results
3.1. Analysis of Correlation and Internal Consistency
3.2. Goodness of Model Fit
3.3. Path Coefficient of Structural Equation Model
3.4. Multi-Group Structural Equation Model Analyses
3.5. The Structural Model’s Direct and Indirect Effects
4. Discussion
- Workload and psychological demands, such as over tasking, time pressure and complex operations, which might directly or indirectly increase risk of occupational stress’ occurrence and development;
- Capital, which mainly includes job autonomy, skills, social support, feedback, job stability and job prospects, such as personal job skills, job autonomy, fair treatment, future development, work stability, sense of identity, respect sense, income and social support;
- Dimension of personality that mainly involves the three typical characteristics of overwhelmed, laid-back, and postponing.
5. Limitations
6. Conclusions
Acknowledgements
Author Contributions
Conflicts of Interest
References
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Dimensions/Items | ± S | Cronbach’s α | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1. Job burden | 2.69 ± 0.71 | 0.863 | 1.00 | |||||||||||
2. Workload | 2.42 ± 0.83 | 0.839 | 0.874 * | 1.00 | ||||||||||
3. PD | 2.97 ± 0.81 | 0.805 | 0.867 * | 0.516 * | 1.00 | |||||||||
4. Capital | 3.50 ± 0.77 | 0.943 | −0.495 * | −0.574 * | −0.284 * | 1.00 | ||||||||
5. Autonomy | 2.46 ± 0.98 | 0.812 | −0.299 * | −0.358 * | −0.161 * | 0.743 * | 1.00 | |||||||
6. Skills | 3.32 ± 0.94 | 0.802 | −0.296 * | −0.369 * | −0.144 * | 0.803 * | 0.579 * | 1.00 | ||||||
7. SS | 3.66 ± 0.81 | 0.903 | −0.329 * | −0.400 * | −0.171 * | 0.777 * | 0.512 * | 0.725 * | 1.00 | |||||
8. Feedback | 3.96 ± 0.85 | 0.869 | −0.528 * | −0.607 * | −0.310 * | 0.878 * | 0.499 * | 0.638 * | 0.610 * | 1.00 | ||||
9. Stability | 3.95 ± 1.01 | 0.754 | −0.417 * | −0.482 * | −0.241 * | 0.773 * | 0.414 * | 0.457 * | 0.466 * | 0.705 * | 1.00 | |||
10. Prospects | 3.68 ± 1.11 | 0.750 | −0.507 * | −0.551 * | −0.331 * | 0.858 * | 0.571 * | 0.531 * | 0.528 * | 0.800 * | 0.657 * | 1.00 | ||
11. Personality | 2.52 ± 0.89 | 0.847 | 0.513 * | 0.495 * | 0.396 * | −0.415 * | −0.308 * | −0.227 * | −0.279 * | −0.411 * | −0.374 * | −0.394 * | 1.00 | |
12. Depression | 1.00 ± 0.55 | 0.889 | 0.366 * | 0.416 * | 0.218 * | −0.506 * | −0.321 * | −0.425 * | −0.489 * | −0.447 * | −0.379 * | −0.407 * | 0.325 * | 1.00 |
13. Well-being | 3.10 ± 1.22 | 0.924 | −0.451 * | −0.449 * | −0.336 * | 0.516 * | 0.418 * | 0.394 * | 0.405 * | 0.443 * | 0.371 * | 0.460 * | −0.419 * | −0.450 * |
Dimensions/Models | df | χ2/df | AGFI | NNFI | IFI | RMSEA | ||
---|---|---|---|---|---|---|---|---|
M1 | Original | 851.09 | 19 | 44.79 | 0.775 | 0.832 | 0.886 | 0.165 |
Modified | 72.50 | 14 | 5.18 | 0.971 | 0.984 | 0.992 | 0.051 | |
M2 | Original | 1001.02 | 41 | 24.42 | 0.836 | 0.864 | 0.899 | 0.120 |
Modified | 221.88 | 36 | 6.16 | 0.955 | 0.970 | 0.980 | 0.057 | |
M3 | Original | 3026.44 | 167 | 18.12 | 0.791 | 0.804 | 0.828 | 0.103 |
Modified | 2308.52 | 163 | 14.16 | 0.836 | 0.849 | 0.871 | 0.090 | |
M4 | Original | 2635.46 | 101 | 26.09 | 0.766 | 0.816 | 0.845 | 0.125 |
Modified | 1801.85 | 97 | 18.58 | 0.878 | 0.871 | 0.896 | 0.104 | |
M5 | Original | 1766.66 | 164 | 10.77 | 0.863 | 0.888 | 0.903 | 0.078 |
Modified | 1018.57 | 160 | 6.37 | 0.919 | 0.938 | 0.948 | 0.058 | |
M6 | Original | 1384.39 | 98 | 14.13 | 0.859 | 0.904 | 0.922 | 0.090 |
Modified | 522.61 | 94 | 5.56 | 0.944 | 0.967 | 0.974 | 0.053 | |
M7 | Original | 2404.31 | 266 | 9.04 | 0.858 | 0.898 | 0.910 | 0.071 |
Modified | 1493.86 | 261 | 5.72 | 0.910 | 0.940 | 0.948 | 0.054 | |
M8 | Original | 2325.27 | 265 | 8.78 | 0.861 | 0.901 | 0.913 | 0.069 |
Modified | 1397.05 | 260 | 5.37 | 0.915 | 0.945 | 0.952 | 0.052 |
Variables | B to D | B to W | C to D | C to W | P to D | P to W | Model Test | |
---|---|---|---|---|---|---|---|---|
Total Sample | 0.19 * | −0.18 * | −0.34 * | 0.31 * | 0.11 * | −0.21 * | ||
Gender | Male | 0.11 | −0.22 * | −0.40 * | 0.27 * | 0.14 * | −0.21 * | p = 0.472 |
Female | 0.27 * | −0.14 * | −0.27 * | 0.34 * | 0.08 | −0.20 * | ||
Marriage | Couple | 0.25 * | −0.21 * | −0.33 * | 0.25 * | 0.10 * | −0.24 * | p = 0.192 |
Single | 0.07 | −0.11 | −0.38 * | 0.39 * | 0.13 * | −0.17 * | ||
Age | <25 years | 0.21 * | −0.19 * | −0.28 * | 0.24 * | 0.11 * | −0.20 * | p = 0.805 |
25–30 years | 0.16 * | −0.17 * | −0.38 * | 0.35 * | 0.10 | −0.21 * | ||
>30 years | 0.21 * | −0.19 * | −0.35 * | 0.30 * | 0.11 * | −0.21 * | ||
Education | <High school | 0.08 | −0.15 * | −0.24 * | 0.15 * | 0.10 * | −0.22 * | p = 0.100 |
Junior high school | 0.25 * | −0.23 * | −0.31 * | 0.32 * | 0.09 | −0.15 * | ||
College and above | 0.13 * | −0.25 * | −0.49 * | 0.31 * | 0.10 * | −0.23 * | ||
Position | Assembly line | 0.16 * | −0.18 * | −0.29 * | 0.22 * | 0.06 | −0.17 * | p = 0.033 |
Other production | 0.30 * | −0.24 * | −0.19 * | 0.24 * | 0.19 * | −0.27 * | ||
Logistical | 0.20 * | −0.23 * | −0.46 * | 0.36 * | 0.06 | −0.19 * |
Dimensions/Effect | Mediator | Outcomes | ||||
---|---|---|---|---|---|---|
Personality | p Value | Depression | p Value | Well-Being | p Value | |
Direct Effect | ||||||
Job burden | 0.52(0.41–0.63) | <0.001 | 0.19 (0.09–0.29) | <0.001 | −0.18 (−0.29–−0.09) | <0.001 |
Capital | −0.14 (−0.24–−0.04) | 0.010 | −0.34 (−0.42–−0.26) | <0.001 | 0.31 (0.23–0.38) | <0.001 |
Character | — | — | 0.11 (0.03–0.19) | 0.006 | −0.21 (−0.28–−0.14) | <0.001 |
Indirect Effect | ||||||
Job burden | — | — | 0.06 (0.02–0.10) | 0.005 | −0.11 (−0.16–−0.07) | <0.001 |
Capital | — | — | −0.02 (−0.03–−0.01) | 0.009 | 0.03 (0.01–0.06) | 0.007 |
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Wang, C.; Li, S.; Li, T.; Yu, S.; Dai, J.; Liu, X.; Zhu, X.; Ji, Y.; Wang, J. Using the Job Burden-Capital Model of Occupational Stress to Predict Depression and Well-Being among Electronic Manufacturing Service Employees in China. Int. J. Environ. Res. Public Health 2016, 13, 819. https://doi.org/10.3390/ijerph13080819
Wang C, Li S, Li T, Yu S, Dai J, Liu X, Zhu X, Ji Y, Wang J. Using the Job Burden-Capital Model of Occupational Stress to Predict Depression and Well-Being among Electronic Manufacturing Service Employees in China. International Journal of Environmental Research and Public Health. 2016; 13(8):819. https://doi.org/10.3390/ijerph13080819
Chicago/Turabian StyleWang, Chao, Shuang Li, Tao Li, Shanfa Yu, Junming Dai, Xiaoman Liu, Xiaojun Zhu, Yuqing Ji, and Jin Wang. 2016. "Using the Job Burden-Capital Model of Occupational Stress to Predict Depression and Well-Being among Electronic Manufacturing Service Employees in China" International Journal of Environmental Research and Public Health 13, no. 8: 819. https://doi.org/10.3390/ijerph13080819