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Table 3 Regression coefficients for the BCSQ-36 and BCSQ-12 models with regard to the 'exhaustion' dimension of the MBI-GS

From: Understanding burnout according to individual differences: ongoing explanatory power evaluation of two models for measuring burnout types

Model/variable

Ry.123

R2 y.123

adj-R2 y.123

F (df1/df2) pa

Se

DW

pb

BCSQ-36

0.74

0.54

0.53

51.01 (9/387) <0.001

0.98

1.82

0.604

 

Ry3.12

Ry(3.12)

T

B (95% CI)

Se

Beta

pc

Intercept

   

−1.83 (−2.91 – -0.76)

0.55

 

0.001

Involvement

<0.01

<0.01

0.51

<0.01 (−0.16 – 0.16)

0.08

<0.01

0.971

Ambition

−0.04

−0.03

0.80

−0.03 (−0.12 – 0.06)

0.05

−0.03

0.475

Overload

0.44

0.34

0.70

0.44 (0.35 – 0.53)

0.05

0.40

<0.001

Indifference

0.18

0.12

0.34

0.25 (0.11 – 0.39)

0.07

0.21

<0.001

L. Development

0.04

0.03

0.39

0.04 (−0.07 – 0.15)

0.06

0.04

0.459

Boredom

−0.06

−0.04

0.41

−0.06 (−0.17 – 0.05)

0.06

−0.06

0.249

Neglect

0.05

0.03

0.40

0.09 (−0.08 – 0.26)

0.09

0.06

0.317

L. Acknowledgement

0.12

0.08

0.49

0.12 (0.02 – 0.21)

0.05

0.12

0.020

L. Control

0.29

0.20

0.57

0.33 (0.22 – 0.44)

0.06

0.27

<0.001

model/variable

Ry.123

R2 y.123

adj-R2 y.123

F (df1/df2) pa

Se

DW

pb

BCSQ-12

0,67

0.45

0.44

105.96 (3/393) <0.001

1.06

1.87

0.177

 

Ry3.12

Ry(3.12)

T

B (95% CI)

Se

Beta

pc

Intercept

   

−1.34 (−1.78 – -0.89)

0.23

 

<0.001

Overload

0.56

0.51

0.97

0.57 (0.48 – 0.65)

0.04

0.51

<0.001

L. Development

0.29

0.23

0.91

0.25 (0.17 – 0.33)

0.04

0.24

<0.001

Neglect

0.25

0.20

0.92

0.32 (0.20 – 0.44)

0.06

0.20

<0.001

  1. Ry.123=multiple correlation coefficient. R2 y.123=coefficient of multiple determination. adj-R2 y.123=adjusted coefficient of multiple determination. pa=p value for variance analysis associated with the regression. Se=standard error. DW=Dubin-Watson value. pb=p value for K-S test for normality contrast on residuals. Ry3.12=partial correlation coefficient. Ry(3.12)=semi-partial correlation coefficient. T=tolerance value. B=regression slope. CI=confidence interval. Beta=standardized slope. pc=p value of Wald test result. The sign < refers to absolute values.