Demographic characteristics
Table 1 Participants’ characteristics
Variables
|
|
N(%)
|
Sex
|
Male
|
960(50.5%)
|
|
Female
|
941(49.5%)
|
Age (years)
|
≤30
|
507(26.7%)
|
|
31–40
|
911(47.9%)
|
|
>40
|
483(25.4%)
|
Marital status
|
Single
|
563(29.6%)
|
|
Married/cohabiting
|
1338(70.4%)
|
Education
|
College
|
410(41.6%)
|
|
Postgraduate or above
|
1491(78.4%)
|
Professional qualifications
|
None
|
210(11%)
|
|
Primary title
|
348(18.3%)
|
|
Intermediate title
|
606(31.9%)
|
|
Senior vice title
|
465(24.5%)
|
|
Senior title
|
272(14.3%)
|
Table 1 shows the demographic characteristics of the subjects. A total of 1,901 doctors completed the measurement of the job performance scale. Among them, there are 960 (50.5%) men and 941 (49.5%) women. The average age of participants in this study was 36.59±7.91 years. Distribution by age: ≤ 30 years old (n=507), 31 to 40 years old (n=911), and >41 years old (n=483). 70.4% of participants are married or living together. 41.6% are university graduates, and 78.4% are masters or above.
Correlation analysis
Table 2 Correlations between sex, age, marital status, education, professional qualifications
Variables
|
1
|
2
|
3
|
4
|
5
|
1. Sex
|
1.000
|
|
|
|
|
2. Age (years)
|
-.104**
|
1.000
|
|
|
|
3. Marital status
|
-.084**
|
.468**
|
1.000
|
|
|
4. Education
|
-.067**
|
.199**
|
.174**
|
1.000
|
|
5. Professional qualifications
|
-.089**
|
.707**
|
.493**
|
.223**
|
1.000
|
Table 2 shows the correlation between these five variables. Gender was negatively correlated with age, marital status, education level, and job title, with significant p-values. These results show that older doctors are more likely to be males, older female doctors are more likely to be single, and male doctors are more educated and job titles. Age is positively correlated with marital status, education level and job title. These results show that older doctors generally have more stable marital status, higher academic qualifications, and job titles than young doctors. Marital status is positively related to education level and professional title. The degree of education is positively related to the professional title.
Measurement Invariance
In this study, four demographic variables of job performance, including gender, age, education level, and professional qualifications, were measured for equivalence tests. Each factor measurement included five models: structural model, factor load invariant model, Project Intercept Invariant Model, Project Residual Invariant Model, and Structural Variance Invariant Model. Table 3 shows the results of the invariance test.
Table 3 Goodness-of-fit statistics for five invariance models
Model
|
χ2
|
Δχ2
|
df
|
Δdf
|
CFI
|
ΔCFI
|
RMSEA
|
RMSEA
[90% CI]
|
|
Sex
|
|
|
|
|
|
|
|
|
|
Male (n = 960)
|
2598.529
|
—
|
492
|
—
|
.900
|
—
|
.067
|
[.064, .069]
|
|
Female (n = 941)
|
2437.617
|
—
|
492
|
—
|
.898
|
—
|
.065
|
[.062, .067]
|
|
Multiple group
|
|
|
|
|
|
|
|
|
|
Configural model
|
5036.145
|
—
|
984
|
—
|
.899
|
—
|
.047
|
[.045, .048]
|
|
Factor loadings invariant model
|
5052.879
|
15.091
|
1014
|
33
|
.900
|
.000
|
.046
|
[.045, .047]
|
|
Item intercepts invariant model
|
5058.970
|
6.091
|
1047
|
33
|
.900
|
.000
|
.045
|
[.044, .046]
|
|
Item residual variance invariant model
|
5077.840
|
18.870
|
1080
|
33
|
.901
|
.001
|
.044
|
[.043, .045]
|
|
Structural covariances invariant model
|
5084.884
|
7.044
|
1086
|
6
|
.901
|
.000
|
.044
|
[.043, .045]
|
|
Age
|
|
|
|
|
|
|
|
|
|
≤30 (n = 507)
|
1569.864
|
—
|
492
|
—
|
.896
|
—
|
.066
|
[.062, .069]
|
|
31–40 (n = 911)
|
2798.198
|
—
|
492
|
|
.877
|
—
|
.072
|
[.069, .074]
|
|
>40 (n = 483)
|
1736.360
|
—
|
492
|
|
.890
|
—
|
.072
|
[.069, .076]
|
Multiple group
|
|
|
|
|
|
|
|
|
|
Configural model
|
6104.553
|
—
|
1476
|
—
|
.885
|
—
|
.041
|
[.040, .042]
|
|
Factor loadings invariant model
|
6172.270
|
67.717
|
1536
|
66
|
.885
|
.002
|
.040
|
[.039, .041]
|
|
Item intercepts invariant model
|
6321.020
|
148.750
|
1602
|
66
|
.883
|
.000
|
.039
|
[.038, .040]
|
|
Item residual variance invariant model
|
6408.253
|
87.233
|
1668
|
66
|
.883
|
.001
|
.039
|
[.038, .040]
|
|
Structural covariances invariant model
|
6431.415
|
23.162
|
1680
|
12
|
.882
|
.001
|
.039
|
[.038, .040]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Note: χ2=Chi-square; df=degrees of freedom; CFI=confirmatory fit index; RMSEA=root mean square error of approximation; CI=90% Confidence Interval.
*indicates statistically-significant difference between nested models based on ΔCFI>|.010|.
Sex
The initial model shows that the Chinese version of the job performance scale applies to the two groups of men and women. The structural covariance invariant model includes these two groups (CFI = 0.901; RMSEA = 0.044). The results of this study report the chi-square for all invariant models (5036.145, 5052.879, 5058.970, 5077.840, 5084.884), and also report the df for all invariant models (984, 1014, 1047, 1080, 1086). Chi-squared differences between the two nested models have also been reported (15.091, 6.091, 18.870, 7.044). All changes in CFI were <0.01, indicating that the Chinese version of the job performance scale is invariant across gender.
Age
The results show that in the three groups of ≤ 30 years old, 31-40 years old and > 40 years old, the CFI value of the initial index of the Chinese version of the job performance scale was less than 0.90. The structural covariance invariant model contains these three groups (CFI = 0.882; RMSEA = 0.039). The results of this study report the chi-squares for all invariant models (6104.553, 6172.270, 6321.020, 6408.253, 6431.415) and also report the df for all invariant models (1476, 1536, 1602, 1668, 1680). Chi-squared differences between two nested models were also reported (67.717, 148.750, 87.233, 23.162). All changes in CFI were <0.01, indicating that the Chinese version of the job performance scale is invariant across age.
Tests for latent mean differences
Finally, we compared latent mean differences in groups by fixing the latent mean values of the males group and the ≤30 group to zero and making a free estimate of the latent means of other groups. The comparison of the sex groups on the latent means revealed no statistically significant differences in the latent means of three factors of the CJPQ. The latent factor means were invariant in the sex groups, revealing that there were no statistically significant differences between males and females on all three subscale scores of the CJPQ. The same result also appeared in the age groups. These results indicated that, on average, there was no difference in the scores of all three subscales of the CJPQ.