Page 21 - Istenič Andreja, Gačnik Mateja, Horvat Barbara, Kukanja Gabrijelčič Mojca, Kiswarday Vanja Riccarda, Lebeničnik Maja, Mezgec Maja, Volk Marina. Ur. 2023. Vzgoja in izobraževanje med preteklostjo in prihodnostjo. Koper: Založba Univerze na Primorskem
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The Role of Mindfulness and Resilience in Predicting Job Burnout
Table 3 Differences in Resilience, Work-Related Burnout, and Dispositional Mindfulness
According to Work Experiences of the Participants
Item Work experience (years) N M SD H p χ2
BRS – . . . . .
CBI-W – . .
MAAS – . .
> . .
– . . . . .
– . .
– . .
> . .
– . . . . .
– . .
– . .
> . .
Notes BRS – Brief Resilience Scale, CBI-W – Copenhagen Burnout Inventory, MAAS – Mindful
Attention Awareness Scale.
Table 4 Regression Analyses Results in Predicting Work-Related Burnout
Item Bβ t
–.**
Mindfulness –. –. –.**
Resilience –. –.
Notes ** p < 0.001.
vice (U = 847.0, Z = –2.239, p < 0.05, r = 0.28). No significant differences were
found in work-related burnout (η2 = 0.012) according to the length of service.
Spearman correlation analyses showed that the studied psychological
variables were significantly correlated with each other. Specifically, work-
related burnout was negatively correlated with mindfulness (r = –0.62, p <
0.001) and resilience (r = –0.54, p < 0.001), while there was a positive correla-
tion between mindfulness and resilience (r = 0.45, p < 0.001).
To determine the predictive value of mindfulness and resilience, we used
multiple regression analyses with the enter method. Preliminary analyses
showed that all the assumptions for performing the regression were met, as
tolerance (0.76) and the variance inflation factor (1.31) indicated that multi-
collinearity was not a concern. Since none of the sociodemographic factors
(age and length of service) were significantly associated with burnout, they
were not included as control variables in subsequent analyses.
Results in table 4 indicated that both mindfulness (β = –0.46, p < 0.001)
21
Table 3 Differences in Resilience, Work-Related Burnout, and Dispositional Mindfulness
According to Work Experiences of the Participants
Item Work experience (years) N M SD H p χ2
BRS – . . . . .
CBI-W – . .
MAAS – . .
> . .
– . . . . .
– . .
– . .
> . .
– . . . . .
– . .
– . .
> . .
Notes BRS – Brief Resilience Scale, CBI-W – Copenhagen Burnout Inventory, MAAS – Mindful
Attention Awareness Scale.
Table 4 Regression Analyses Results in Predicting Work-Related Burnout
Item Bβ t
–.**
Mindfulness –. –. –.**
Resilience –. –.
Notes ** p < 0.001.
vice (U = 847.0, Z = –2.239, p < 0.05, r = 0.28). No significant differences were
found in work-related burnout (η2 = 0.012) according to the length of service.
Spearman correlation analyses showed that the studied psychological
variables were significantly correlated with each other. Specifically, work-
related burnout was negatively correlated with mindfulness (r = –0.62, p <
0.001) and resilience (r = –0.54, p < 0.001), while there was a positive correla-
tion between mindfulness and resilience (r = 0.45, p < 0.001).
To determine the predictive value of mindfulness and resilience, we used
multiple regression analyses with the enter method. Preliminary analyses
showed that all the assumptions for performing the regression were met, as
tolerance (0.76) and the variance inflation factor (1.31) indicated that multi-
collinearity was not a concern. Since none of the sociodemographic factors
(age and length of service) were significantly associated with burnout, they
were not included as control variables in subsequent analyses.
Results in table 4 indicated that both mindfulness (β = –0.46, p < 0.001)
21
