| Literature DB >> 27509514 |
Xiaoshi Yang1, Lutian Yao2, Hui Wu3, Yang Wang4, Li Liu5, Jiana Wang6, Lie Wang7.
Abstract
With the global economic crisis and industrial restructuring, the unemployed are suffering from job loss-related stress and loss of income, which is believed to impair their mental and physical health, while coping and self-efficacy could combat the adverse effects of unemployment on health. Thus, this study aims to describe quality of life (QOL) among unemployed Chinese people and explore the associated factors. A cross-sectional study was conducted by convenience sampling, composed of 1825 unemployed people, from January 2011 to September 2011. Questionnaires pertaining to demographic characteristics, the 36-item Short-Form Health Survey (SF-36), the abbreviated version of the Cope Inventory (Brief COPE) and self-efficacy scales were used to collect information from unemployed people in the eastern, central, and western regions of China. Hierarchical multiple regression analysis was performed to explore the related factors of QOL. A structural equation model (SEM) was used to test the relations among coping, self-efficacy, and QOL. Mental QOL was significantly lower than physical QOL in Chinese unemployed people. Coping had significant effects on both physical component summary (PCS) and mental component summary (MCS), while self-efficacy played the mediating role in the association between Coping and QOL. Unemployed Chinese people's mental QOL was disrupted more seriously than their physical QOL. An increase in coping could improve QOL by promoting better management of issues brought about by unemployment. In addition, self-efficacy has the ability to reduce the impact of unemployment on QOL, through the mediating path of coping on QOL. This study highlights the need of coping skills training and self-efficacy enhancement for better management of unemployment in order to improve QOL and well-being.Entities:
Keywords: MCS; PCS; QOL; coping; self-efficacy; the unemployed
Mesh:
Year: 2016 PMID: 27509514 PMCID: PMC4997483 DOI: 10.3390/ijerph13080797
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Demographic characteristics of unemployed people (N = 1825).
| Variables | Number ( | Percent (%) |
|---|---|---|
| Male | 1022 | 56.00 |
| Female | 803 | 44.00 |
| <25 | 367 | 20.11 |
| 25–39 | 806 | 44.16 |
| >39 | 652 | 35.73 |
| Married | 1073 | 58.79 |
| Others | 752 | 41.21 |
| ≤senior high school | 1156 | 63.34 |
| >senior high school | 669 | 36.66 |
| ≤1000 | 417 | 22.85 |
| 1001–1500 | 391 | 21.42 |
| 1501–2000 | 420 | 23.01 |
| >2000 | 597 | 32.71 |
| Yes | 994 | 54.47 |
| No | 831 | 45.53 |
| 1–2 | 387 | 21.21 |
| 3–5 | 372 | 20.38 |
| 6–11 | 454 | 24.88 |
| ≥12 | 612 | 33.53 |
| Physical function | 84.3 ± 19.7 | |
| Role limitation due to physical problems | 65.4 ± 33.3 | |
| Bodily pain | 72.9 ± 22.0 | |
| General perception of health | 61.4 ± 18.4 | |
| Energy and vitality | 61.0 ± 17.8 | |
| Social functioning | 70.1 ± 20.4 | |
| Role limitation due to emotional problems | 58.4 ± 36.6 | |
| Mental health | 59.6 ± 17.6 |
QOL scores of unemployed people on demographic characteristics (N = 1825).
| Variables | PCS | MCS |
|---|---|---|
| Male | 71.8 ± 17.6 | 62.9 ± 17.1 |
| Female | 70.2 ± 17.2 * | 61.9 ± 16.5 |
| <25 | 77.6 ± 14.8 ** | 64.5 ± 15.6 * |
| 25–39 | 71.4 ± 16.7 * | 61.7 ± 16.2 |
| >39 | 66.9 ± 18.5 | 62.1 ± 18.3 |
| Married | 69.2 ± 17.4 ** | 62.5 ± 17.2 |
| Others | 73.8 ± 16.3 | 62.3 ± 15.9 |
| ≤senior high school | 69.6 ± 17.3 ** | 62.1 ± 17.0 |
| >senior high school | 73.6 ± 16.4 | 63.1 ± 16.3 |
| ≤1000 | 67.0 ± 18.1 ** | 58.7 ± 17.1 ** |
| 1001–1500 | 70.3 ± 17.3 * | 61.5 ± 16.8 * |
| 1501–2000 | 71.0 ± 17.5 * | 63.1 ± 16.3 |
| >2000 | 74.4 ± 16.4 | 65.1 ± 16.7 |
| Yes | 64.0 ± 17.3 ** | 59.2 ± 16.8 ** |
| No | 76.8 ± 15.4 | 65.0 ± 16.5 |
| 1–2 month | 76.2 ± 15.7 | 65.1 ± 16.8 |
| 3–5month | 73.8 ± 16.0 * | 63.8 ± 15.2 * |
| 6–11 month | 70.2 ± 17.5 ** | 62.0 ± 15.6 * |
| ≥12 month | 66.9 ± 18.2 ** | 60.0 ± 18.4 ** |
* p < 0.05; ** p < 0.01.
Correlation of PCS and MCS and related factors.
| Mean | SD | PCS | MCS | Adaptive Coping | Maladaptive Coping | Self-Efficacy | |
|---|---|---|---|---|---|---|---|
| 71.1 | 17.4 | 1 | |||||
| 62.4 | 16.9 | 0.620 ** | 1 | ||||
| 45.7 | 7.2 | 0.275 ** | 0293 ** | 1 | |||
| 40.6 | 6.9 | −0.140 ** | −0.193 ** | 0.400 ** | 1 | ||
| 38.3 | 5.7 | 0.332 ** | 0.450 ** | 0.259 ** | −0.220 ** | 1 |
** p < 0.01.
The hierarchical multiple regression models of PCS and MCS.
| Variables | PCS | MCS | ||||
|---|---|---|---|---|---|---|
| Model 1 b(B) | Model 2 b(B) | Model 3 b(B) | Model 1 b(B) | Model 2 b(В) | Model 3 b(B) | |
| 77.334 ** | 61.775 ** | 42.673 ** | 73.377 ** | 61.306 ** | 28.244 ** | |
| −1.800 * (−0.051) | −1.891 * (−0.054) | −1.541 * (−0.044) | −1.289 (−0.038) | −1.366 (−0.040) | −0.822 (−0.024) | |
| 25–39 vs. <25 | −3.287 ** (−0.094) | −1.574 (−0.045) | −1.630 (−0.046) | −2.437 * (−0.072) | −0.493 (−0.015) | −0.454 (−0.013) |
| >39 vs. <25 | −2.615 (−0.072) | −1.182 (−0.032) | −1.375 (−0.038) | 0.414 (0.012) | 2.336 (0.066) | 1.974 (0.056) |
| −0.045 (−0.001) | 0.687 (0.019) | 0.756 (0.021) | −2.486 * (−0.073) | −1.628 (−0.048) | −1.449 (−0.042) | |
| 0.847 (0.023) | 0.609 (0.017) | 0.347 (0.010) | −0.251 (−0.007) | −0.564 (−0.016) | −1.027 (−0.029) | |
| −10.876 ** (−0.311) | −10.159 ** (−0.290) | −9.891 ** (−0.282) | −5.737 ** (−0.170) | −5.049 ** (−0.149) | −4.562 ** (−0.135) | |
| 1001–1500 vs. ≤1000 | 2.300 (0.054) | 2.295 * (0.054) | 2.332 * (0.055) | 2.386 * (0.058) | 2.252 * (0.055) | 2.403 * (0.059) |
| 1501–2000 vs. ≤1000 | 3.043 ** (0.074) | 2.100 (0.051) | 2.211 * (0.053) | 4.005 ** (0.100) | 2.718 * (0.068) | 3.016 ** (0.076) |
| >2000 vs. ≤1000 | 5.031 ** (0.136) | 3.627 ** (0.098) | 3.116 ** (0.084) | 5.206 ** (0.145) | 3.211 ** (0.089) | 2.476 * (0.069) |
| 3–5 vs. 1–2 | −0.317 (−0.007) | 0.474 (0.011) | 0.698 (0.016) | −0.698 (−0.017) | 0.415 (0.010) | 0.771 (0.019) |
| 6–11 vs. 1–2 | −2.487 * (−0.061) | −1.567 (−0.039) | −1.256 (−0.031) | −1.973 (−0.050) | −0.844 (−0.022) | −0.258 (−0.007) |
| ≥12 vs. 1–2 | −3.763 ** (−0.102) | −3.541 ** (−0.096) | −3.283 ** (−0.089) | −3.807 ** (−0.107) | −3.576 ** (−0.100) | −3.009 ** (−0.084) |
| Adaptive coping | 0.856 ** (0.344) | 0.684 ** (0.275) | 0.973 ** (0.407) | 0.682 ** (0.285) | ||
| Maladaptive coping | −0.639 ** (−0.248) | −0.473 ** (−0.184) | −0.860 ** (−0.348) | −0.573 ** (−0.232) | ||
| 0.531 ** (0.174) | 0.906 ** (0.306) | |||||
| 0.167 | 0.281 | 0.304 | 0.061 | 0.235 | 0.308 | |
| 0.167 | 0.114 | 0.023 | 0.061 | 0.174 | 0.073 | |
* p < 0.05; ** p < 0.01.
Figure 1Structural equation modeling of coping and QOL (PCS and MCS).
Figure 2Structural equation modeling of mediating role of self-efficacy on the association between coping and QOL (PCS and MCS).