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

Table 4 Regression coefficients for the BCSQ-36 and BCSQ-12 models with regard to the ‘cynicism’ dimension of the MBI-GS

Model/variable	R_y.123	R² _y.123	adj-R² _y.123	F (df₁/df₂) p^a	Se	DW	p^b
BCSQ-36	0.77	0.60	0.59	64.43 (9/387) <0.001	1.02	2.04	0.211
	R_y3.12	R_y(3.12)	T	B (95% CI)	Se	Beta	p^c
Intercept				−1.21 (−2.33 – -0.08)	0.57		0.036
Involvement	−0.10	−0.06	0.51	−0.16 (−0.33 – 0.01)	0.09	−0.08	0.059
Ambition	−0.03	−0.02	0.80	−0.03 (−0.12 – 0.07)	0.05	−0.02	0.560
Overload	0.03	0.02	0.70	0.03 (−0.07 – 0.12)	0.05	0.02	0.549
Indifference	0.34	0.23	0.34	0.53 (0.39 – 0.68)	0.07	0.40	<0.001
L. Development	0.17	0.11	0.39	0.20 (0.08 – 0.32)	0.06	0.17	0.001
Boredom	−0.03	−0.02	0.41	−0.04 (−0.15 – 0.08)	0.06	−0.03	0.501
Neglect	−0.04	−0.02	0.40	−0.07 (−0.24 – 0.11)	0.09	−0.04	0.465
L. Acknowledgement	0.24	0.16	0.49	0.25 (0.15 – 0.36)	0.05	0.22	<0.001
L. Control	0.22	0.14	0.57	0.26 (0.14 – 0.37)	0.06	0.19	<0.001
model/variable	R_y.123	R² _y.123	adj-R² _y.123	F (df₁/df₂) p^a	Se	DW	p^b
BCSQ-12	0.67	0.45	0.44	106.12 (3/393) <0.001	1.19	2.00	0.048
	R_y3.12	R_y(3.12)	T	B (95% CI)	Se	Beta	p^c
Intercept				−1.83 (−2.33 – -1.34)	0.25		<0.001
Overload	0.14	0.11	0.97	0.13 (0.04 – 0.22)	0.05	0.11	0.005
L. Development	0.55	0.48	0.91	0.59 (0.50 – 0.68)	0.05	0.51	<0.001
Neglect	0.34	0.27	0.92	0.49 (0.35 – 0.63)	0.07	0.28	<0.001

R_y.123=multiple correlation coefficient. R² _y.123=coefficient of multiple determination. adj-R² _y.123=adjusted coefficient of multiple determination. p^a=p value for variance analysis associated with the regression. Se=standard error. DW=Dubin-Watson value. p^b=p value for K-S test for normality contrast on residuals. R_y3.12=partial correlation coefficient. R_y(3.12)=semi-partial correlation coefficient. T=tolerance value. B=regression slope. CI=confidence interval. Beta=standardized slope. p^c=p value of Wald test result. The sign < refers to absolute values.

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