Demographic Characteristics of Participants
The social and demographic characteristics of 2693 village doctor are shown in table 2. The average age of them were 44.64 ±7.25years, and 64.42% were male and the largest proportion of them (48.36%) were in the 40~49 age group, conversely, the proportion aged 30 and under was as low as 1.30% percent. The majority of respondents were married (94.75%), more than half of them had only technical secondary school education (68.18%), and 3.76% of village doctors had middle and senior professional titles, whereas 91.80% had junior professional titles or no professional titles. 41.13% of the respondents had worked between 20 and 29 years, 46.46% of them earned less than 2,000 yuan per month, but 69.86% of them needed to work 60 hours or more a week.
Table 2. Demographic characteristics of participants (n =2693).
Socio-Demographic Information
|
N
|
%
|
Gender
|
|
|
Male
|
1736
|
64.42
|
Female
|
922
|
34.27
|
Missing
|
35
|
1.30
|
Age, Group
|
|
|
<30
|
36
|
1.30
|
30~
|
624
|
23.17
|
40~
|
1302
|
48.36
|
50~
|
685
|
25.45
|
Missing
|
46
|
1.71
|
Marital status
|
|
|
Unmarried
|
68
|
2.50
|
Married
|
2551
|
94.75
|
Missing
|
72
|
2.75
|
Education background
|
|
|
University or above
|
71
|
2.61
|
Junior College
|
658
|
24.41
|
Technical secondary school
|
1836
|
68.18
|
Lower than senior school
|
91
|
3.38
|
Missing
|
37
|
1.38
|
Professional ranks and titles
|
|
|
Senior title
|
15
|
0.57
|
Mid-level title
|
86
|
3.19
|
Primary title
|
1306
|
48.50
|
No title
|
1166
|
43.30
|
Missing
|
120
|
4.46
|
Years of work
|
|
|
<5
|
24
|
0.89
|
5-9
|
63
|
2.34
|
10-19
|
830
|
30.92
|
20-29
|
1104
|
41.13
|
>30
|
587
|
21.87
|
Missing
|
76
|
2.83
|
monthly income(yuan)
|
|
|
<1000
|
311
|
11.59
|
1000~
|
939
|
34.87
|
2000~
|
769
|
28.58
|
3000~
|
506
|
18.82
|
Missing
|
168
|
6.14
|
Average weekly working hours
|
|
|
<40
|
390
|
14.46
|
40~
|
336
|
12.52
|
60~
|
1880
|
69.86
|
Missing
|
87
|
3.16
|
Descriptive Analysis of Study Variable
The total item scores of job satisfaction, resilience, work engagement and turnover intention were 32.48±8.93, 74.01±17.06, 66.14±20.26 and 12.16±6.09 respectively. The item scores contained in each dimension are shown in table 3. According to the scores, 722(26.8%) of the village doctor had low turnover intention, 708(26.3%) of them had moderate turnover intention, 1263(46.9) had high turnover intention. Job satisfaction in workload (3.79±1.50), promotion (3.74±1.53), income (3.54±1.55), social security (3.70±1.28) was lower than the other items.
Table 3. Item scores in job satisfaction, resilience, work engagement and turnover intention.
Items
|
Mean±SD
|
Job satisfaction
|
32.48±8.93
|
Workload
|
3.79±1.50
|
Colleagues
|
4.71±1.30
|
Superiors
|
4.72±1.37
|
Environment and Facility
|
4.12±1.44
|
promotion
|
3.74±1.53
|
Income
|
3.54±1.55
|
Social Security
|
3.70±1.28
|
Training opportunities
|
4.16±1.28
|
Resilience
|
74.01±17.06
|
Tenacity
|
37.53±9.79
|
Strength
|
23.93±5.66
|
Optimism
|
12.54±3.06
|
Work engagement
|
66.14±20.26
|
Work vigor
|
23.56±7.02
|
Work dedication
|
19.7±6.28
|
Work absorption
|
22.87±7.63
|
Turnover intention
|
12.16±6.09
|
Thought of leaving the organization you served now
|
3.11±1.59
|
Thought of leaving this industry
|
3.11±1.62
|
Looking for a new job recently
Looking for a new job next year
|
3.05±1.64
2.88±1.61
|
Correlations of Study Variables
The correlation coefficient between variables are shown Table 4. Job satisfaction was positively correlated with resilience and work engagement, and negatively correlated with turnover intension. Resilience was positively correlated with work engagement and negatively correlated with turnover intension. work engagement was negatively correlated with turnover intension.
Table 4. Correlation coefficients among study variables.
|
Items
|
Job Satisfaction
|
Resilience
|
Work Engagement
|
Turnover Intention
|
Job Satisfaction
|
|
|
|
|
Resilience
|
0.45**
|
|
|
|
Work Engagement
|
0.41**
|
0.67**
|
|
|
Turnover Intention
|
-0.39**
|
-0.24**
|
-0.27**
|
|
* p < 0.01.
|
Test of Study Model
The SEM was constructed to interlink and assess the relationship among the four variables (job satisfaction, resilience, work engagement, turnover intention). The data and theoretical model were fitted by generalized least square method, and the theoretical model was modified according to the model fitting index. The relationship and valid path among four variables were indicated in the final model (figure 2). The final modified hypothetical model’s fit indices were AGFI = 0.911, GFI = 0.935, NFI = 0.964, CFI = 0.966, IFI = 0.966, TLI = 0.959, RMSEA = 0.068, and all of them are complied with reference value, which presented it as an acceptable model fit.
(Locate Figure2. The final model and standardized model paths)
Each path was guided by 2000 repetitions of Bias-corrected bootstrap using maximum likelihood estimation, and the results of mediation analysis are shown in table 5. The mediation effect has statistical significance when the 95% CI of the estimation of the mediate effect does not include 0. Job satisfaction had a direct positive effect on work engagement (β= 0.11, p < 0.001) and a negative effect on turnover intention (β= -0.37, p < 0.001). Work engagement had a direct negative effect on turnover intention (β= -0.13, p < 0.002). Job satisfaction had a direct positive effect on resilience (β= 0.51, p < 0.001), and resilience had a direct positive effect on work engagement (β= 0.63, p < 0.001), but had no direct effect on turnover intension (β= -0.03, p =0.03). Thus, except hypothesis 5, the final result supported all hypotheses.
Table 5. Significance test of the mediating test.
Model Pathways Estimated 95% CI
Total effects
Resilience←Job satisfaction 0.51 0.47–0.55
Work engagement←Job satisfaction 0.44 0.39–0.47
Turnover intention←Job satisfaction ﹣0.42 (﹣0.46)–(﹣0.37)
Work engagement←Resilience 0.63 0.59–0.68
Turnover intention←Resilience ﹣0.06 (﹣0.11) –(﹣0.01)
Turnover intention←Work engagement ﹣0.13 (﹣0.19)–(﹣0.07)
Direct effects
Resilience←Job satisfaction 0.51 0.47–0.55
Work engagement←Job satisfaction 0.11 0.07–0.16
Turnover intention←Job satisfaction ﹣0.37 (﹣0.42)–(﹣0.32)
Work engagement←Resilience 0.63 0.59–0.68
Turnover intention←Resilience 0.03 (﹣0.04)–0.09
Turnover intention←Work engagement ﹣0.13 (﹣0.19)–(﹣0.07)
Indirect effects
Work engagement←Job satisfaction 0.32 0.29–0.36
Turnover intention←Job satisfaction ﹣0.04 (﹣0.07)–(﹣0.02)
Turnover intention←Resilience ﹣0.09 (﹣0.12)–(﹣0.04)
Regarding the path between job satisfaction and Turnover intention, the direct and indirect effect of this path was statistically significant, which means the mediate effect exists. However, the direct effect between resilience and turnover intention was not significant, indicating that the model supports the hypothesis that between job satisfaction and turnover intention, work engagement has a significant mediate effect but resilience has no mediate effect. However, in-depth studies have found that resilience can indirectly affect turnover intention through the mediating role of work engagement. Table 6 shows that the estimated 95%CI of the three mediation paths does not include 0, verifies the above analysis of the effect among job satisfaction, resilience, work engagement and turnover intention.
Table 6. Significance test of every mediating pathway.
Model Pathways 95% CI
Turnover intention←Resilience←Job satisfaction (﹣0.02)–0.06
Turnover intention←Work engagement←Job satisfaction (﹣0.03)–(﹣0.01)
Work engagement←Resilience←Job satisfaction 1.90–2.41
Turnover intention←Work engagement←Resilience (﹣0.02)–(﹣0.01)