Proactive personality, regulatory focus and self-efficacy and their relationship with job crafting: Correlations and descriptive analyses
As observed in Table 1, proactive personality correlated positively with all the regulatory focus components, both in promotion and prevention. Furthermore, proactive personality was related positively to self-efficacy. The Job Crafting dimensions were positively correlated in all cases with proactive personality: Increasing structural job resources, Decreasing hindering job demands, Increasing social job resources, and Increasing challenging job demands.
Self-efficacy showed positive correlations with four elements of the regulatory focus, and also with the dimensions of Job Crafting. Finally, the relationships established between the components of regulatory focus and Job Crafting were positive and significant in all cases.
Table 1. Proactive personality, Regulatory focus, Self-efficacy, and Job Crafting. Correlations and descriptive statistics
|
PP
|
ONT
|
A
|
OEO
|
SO
|
SE
|
IStJR
|
DHJD
|
ISoJR
|
IChJD
|
PP
|
̶
|
|
|
|
|
|
|
|
|
|
ONT
|
.69***
|
̶
|
|
|
|
|
|
|
|
|
A
|
.45***
|
.42***
|
̶
|
|
|
|
|
|
|
|
OEO
|
.24***
|
.33***
|
.29***
|
̶
|
|
|
|
|
|
|
SO
|
.60***
|
.57***
|
.51***
|
.38***
|
̶
|
|
|
|
|
|
SE
|
.66***
|
.51***
|
.33***
|
.11***
|
.50***
|
̶
|
|
|
|
|
IStJR
|
.65***
|
.56***
|
.45***
|
.23***
|
.68***
|
.59***
|
̶
|
|
|
|
DHJD
|
.31***
|
.30***
|
.20***
|
.34***
|
.13**
|
.25***
|
.26***
|
̶
|
|
|
ISoJR
|
.29***
|
.32***
|
.17***
|
.43***
|
.20***
|
.20***
|
.24***
|
.51***
|
̶
|
|
IChJD
|
.57***
|
.59***
|
.33***
|
.28***
|
.43***
|
.46***
|
.56***
|
.36***
|
.46***
|
̶
|
M
|
82.47
|
4.81
|
4.76
|
4.43
|
5.55
|
31.47
|
4.71
|
3.91
|
3.83
|
4.58
|
SD
|
14.21
|
1.03
|
.94
|
1.36
|
.96
|
4.91
|
.81
|
1.34
|
1.26
|
1.16
|
Note. PP= Proactive personality; ONT= Openness to new things; A= Autonomy; OEO= Orientation to the expectations of others; SO= Sense of obligation; SE= Self-efficacy; IStJR = Increasing structural job resources; DHJD = Decreasing hindering job demands; ISoJR = Increasing social job resources; IChJD = Increasing challenging job demands. **p < .01; ***p < .001.
Burnout profiles: Differences in individual variables and in Job Crafting
First, the mean scores for the study sample in the Burnout dimensions were: Personal impact (M=2.11), Personal dissatisfaction (M=2.14); Quitting motivation (M=2.37), and Social climate (M=3.93). A two-stage cluster analysis performed to classify the cases by scores on the Burnout dimensions (Figure 1) found two groups or clusters.
The first cluster (C1), made up of 21.5% of the cases (n=138), was characterized by scoring above the overall mean in the Personal impact (M=3.05), Personal dissatisfaction (M=2.95), and Quitting motivation (M=3.05) dimensions, and lower than the sample mean score in Social climate (M=3.41).
The second cluster (C2), with 78.5% of the cases (n=505), was defined by scores below the sample mean in Personal impact (M=1.85), Personal dissatisfaction (M=1.92), and quitting motivation (M=2.18); and a score higher than the mean in Social climate (M=4.07).
Titles: Figure 1. Cluster composition
Legends: Note. Factors in order of importance of input. (*) Cluster comparisons.
Table 2 shows the mean scores on the individual variables and the Job Crafting components when the Burnout profiles found based on the cluster analysis were compared. As observed, Cluster 2 has significantly higher scores than Cluster 1 in Proactive personality, Openness to new things, Autonomy, Sense of obligation, Self-efficacy, Increasing structural job resources, Increasing social job resources, and Increasing challenging job demands. No statistically significant differences were found between Burnout profiles for the regulatory focus Orientation to the expectations of others factor, and for the Job Crafting Decreasing hindering job demands dimension.
Table 2. Proactive personality, Regulatory focus, Self-efficacy and Job Crafting. Descriptive statistics and t test by Burnout profile
|
Burnout
|
t
|
p
|
d
|
C1
|
C2
|
N
|
Mean
|
SD
|
N
|
Mean
|
SD
|
PP
|
138
|
74.59
|
17.53
|
505
|
84.62
|
12.33
|
-6.30
|
.000
|
.61
|
ONT
|
138
|
4.33
|
1.22
|
505
|
4.94
|
.93
|
-5.46
|
.000
|
.53
|
A
|
138
|
4.47
|
1.22
|
505
|
4.84
|
.84
|
-3.32
|
.001
|
.32
|
OEO
|
138
|
4.42
|
1.43
|
505
|
4.44
|
1.34
|
-.15
|
.874
|
-
|
SO
|
138
|
5.04
|
1.33
|
505
|
5.68
|
.78
|
-5.38
|
.000
|
.52
|
SE
|
138
|
29.17
|
6.25
|
505
|
32.10
|
4.27
|
-5.17
|
.000
|
.50
|
IStJR
|
138
|
4.06
|
1.10
|
505
|
4.89
|
.60
|
-8.42
|
.000
|
.81
|
DHJD
|
138
|
3.76
|
1.22
|
505
|
3.95
|
1.36
|
-1.53
|
.125
|
-
|
ISoJR
|
138
|
3.60
|
1.23
|
505
|
3.89
|
1.26
|
-2.35
|
.019
|
.23
|
IChJD
|
138
|
3.98
|
1.25
|
505
|
4.74
|
1.07
|
-7.16
|
.000
|
.69
|
Note. PP= Proactive personality; ONT= Openness to new things; A= Autonomy; OEO= Orientation to the expectations of others; SO= Sense of obligation; SE= Self-efficacy; IStJR = Increasing structural job resources; DHJD = Decreasing hindering job demands; ISoJR = Increasing social job resources; IChJD = Increasing challenging job demands.
Multiple linear regression models for Burnout
In the Personal impact dimension, two models resulted, the second of which explained 16.6% of the variance (R2=.16). The validity of the model, as determined by the Durbin-Watson D, was 2.07. According to the standardized coefficients, Increasing structural job resources had the most explanatory value.
In Job dissatisfaction, as observed in the table, two models were found. In the second, the explained variance was 19.7% (R2=.19) and the D=2.13, confirming the model’s validity. In this case, Increasing structural job resources was the strongest predictor in the equation.
For Quitting motivation, the regression analysis revealed a single model, where the Increasing structural job resources variable was the only one which entered the equation, with an explained variance of 15.7% (R2=.15). The Durbin-Watson D=1.93.
Finally, for the Social climate dimension of Burnout, two models were found in the regression analysis, where the second of them showed an explanatory value of 18.9% (R2=.18) and with D=1.95, confirming the model’s validity.
Table 3. Stepwise Multiple Linear Regression Models for the Burnout dimensions
IMPACTO PERSONAL
|
Model
|
R
|
R2
|
Corrected R2
|
Change statistics
|
Durbin Watson
|
Standard error of estimation
|
Change in R2
|
Change in F
|
Sig. of change in F
|
1
|
.40
|
.16
|
.15
|
.64
|
.16
|
122.21
|
.000
|
2.07
|
2
|
.40
|
.16
|
.16
|
.64
|
.00
|
4.55
|
.033
|
Modelo 2
|
Unstandardized coefficients
|
Standardized coefficients
|
t
|
Sig.
|
Collinearity
|
B
|
Std. error
|
Beta
|
Tol.
|
VIF
|
(Constant)
|
3.93
|
.17
|
|
22.32
|
.000
|
|
|
IStJR
|
-.29
|
.03
|
-.34
|
-7.68
|
.000
|
.65
|
1.53
|
SE
|
-.01
|
.00
|
-.09
|
-2.13
|
.033
|
.65
|
1.53
|
INSATISFACCIÓN LABORAL
|
Model
|
R
|
R2
|
Corrected R2
|
Change statistics
|
Durbin Watson
|
Standard error of estimation
|
Change in R2
|
Change in F
|
Sig. of change in F
|
1
|
.43
|
.19
|
.19
|
.58
|
.19
|
152..32
|
.000
|
2.13
|
2
|
.44
|
.19
|
.19
|
.58
|
.00
|
4.03
|
.045
|
Model 2
|
Unstandardized coefficients
|
Standardized coefficients
|
t
|
Sig.
|
Collinearity
|
B
|
Std. error
|
Beta
|
Tol.
|
VIF
|
(Constant)
|
3.90
|
.14
|
|
26.38
|
.000
|
|
|
IStJR
|
-.29
|
.03
|
-.37
|
-8.02
|
.000
|
.57
|
1.75
|
PP
|
-.00
|
.00
|
-.09
|
-2.00
|
.045
|
.57
|
1.75
|
ABANDONO MOTIVACIONAL
|
Model
|
R
|
R2
|
Corrected R2
|
Change statistics
|
Durbin Watson
|
Standard error of estimation
|
Change in R2
|
Change in F
|
Sig. of change in F
|
1
|
.39
|
.15
|
.15
|
.58
|
.15
|
119.75
|
.000
|
1.93
|
Model 1
|
Unstandardized coefficients
|
Standardized coefficients
|
t
|
Sig.
|
Collinearity
|
B
|
Std. error
|
Beta
|
Tol.
|
VIF
|
(Constant)
|
3.81
|
.13
|
|
28.43
|
.000
|
|
|
IStJR
|
-.30
|
.02
|
-.39
|
-10.94
|
.000
|
1.00
|
1.00
|
CLIMA SOCIAL
|
Model
|
R
|
R2
|
Corrected R2
|
Change statistics
|
Durbin Watson
|
Standard error of estimation
|
Change in R2
|
Change in F
|
Sig. of change in F
|
1
|
.42
|
.18
|
.18
|
.56
|
.18
|
142.14
|
.000
|
1.95
|
2
|
.43
|
.18
|
.18
|
.56
|
.00
|
5.66
|
.018
|
Model 2
|
Unstandardized coefficients
|
Standardized coefficients
|
t
|
Sig.
|
Collinearity
|
B
|
Std. error
|
Beta
|
Tol.
|
VIF
|
(Constant)
|
2.30
|
.13
|
|
17.01
|
.000
|
|
|
IStJR
|
.31
|
.02
|
.40
|
11.03
|
.000
|
.94
|
1.06
|
ISoJR
|
.04
|
.01
|
.08
|
2.38
|
.018
|
.94
|
1.06
|
Mediation models
Based on these results, we saw a need to evaluate whether, in those cases where more than one variable was included in the equation, the factors with the least predictive value were acting as mediators in the effect of the IStJR dimension of Job Crafting on the Burnout components. To find out, we computed simple mediation models, in which the mediators were the factors involved in the corresponding equation in each case.
Figure 2 shows the simple mediation model for Personal impact. The first regression analysis estimated the effect of the IStJR dimension with Self-efficacy as the result variable (M), and was found to be significant β=3.54, p<.001). The following regression analysis, taking Personal impact as the result variable (Y), estimated the effect of the independent variable β=-.29 p<.001 and the mediator β=-.01, p<.05, which were statistically significant in both cases.
The total effect of the model was significant β=-.34 p<.001. Finally, the analysis of indirect effects using bootstrapping found a no significant effect β=-.04, SE=.02, 95% CI (-.100, .001).
Titles: Figure 2. A simple mediation model of Self-efficacy on the relationship between the IStJR dimension of Job Crafting and Personal impact of burnout
In Figure 3, the mediation model proposed for job dissatisfaction showed a significant relationship between the IStJR dimension of Job Crafting (X) and Proactive personality (M): β= 11.39, p<.001. The estimate of the direct effect X→Y demonstrated the existence of significance in the relationship β= -.29, p<.001. In addition, the estimation of the M→Y effect was also significant β=-.004, p<.05, although with a small magnitude. With the analysis of indirect effect (X→M→Y), using bootstrapping, no significant values were found β= -.04, SE=.02, 95% CI (-.102, .002).
Titles: Figure 3. Simple mediation model of Proactive personality on the relationship between the IStJR dimension of Job Crafting and Job dissatisfaction of Burnout
Finally, Figure 4 shows the simple mediation model for Social climate, as another of the dimensions of burnout. In the first regression analysis, the result variable was the ISoJR dimension of Job Crafting (M), and the effect of the IStJR dimension was estimated, finding it to be significant β=.37, p<.001. With the following regression analysis, taking Social climate as the result variable (Y), the effects of the independent variable β=.30, p<.001 and the mediator β=.04, p<.05 were estimated, with a total effect of the model of β=.32, p<.001. Finally, based on the indirect effect analysis, in this case, the effect was significant β=.01, SE=.007, 95% CI (.002, .032).
Titles: Figure 4. Simple mediation model for ISoJR on the relationship between the IStJR dimension of Job Crafting and Social climate of burnout