Table 5.

Binary logistic regression with the criterion IGD_cand/RG.

	Wald (df = 1)	p	OR	OR 95% CI Lower	OR 95% CI Upper	∆R2	χ2	df	p
Model 1a						0.023	6.22	2	< 0.001
Constant	1.18	0.277	0.683
Age	24.27	< 0.001	0.958	0.942	0.974
Sexb	4.49	0.034	0.591	0.364	0.961
Model 2						0.024	32.70	3	< 0.001
Constant	4.86	0.027	2.50
Age	23.74	< 0.001	0.958	0.942	0.975
Sexb	4.02	0.045	0.606	0.372	0.989
PSS	34.22	< 0.001	0.942	0.924	0.961
Model 3						0.090	129.92	7	< 0.001
Constant	15.07	< 0.001	0.061
Age	11.46	0.001	0.969	0.952	0.987
Sexb	3.32	0.069	0.621	0.371	1.037
PSS	16.92	< 0.001	0.956	0.936	0.977
MOGQ social	0.00	0.986	1.000	0.958	1.044
MOGQ escapism	19.94	< 0.001	1.127	1.070	1.188
MOGQ competition	32.29	< 0.001	1.150	1.096	1.207
MOGQ coping	2.29	0.130	0.951	0.891	1.015
MOGQ skills	0.02	0.899	0.998	0.962	1.035
MOGQ fantasy	6.91	0.009	1.054	1.013	1.096
MOGQ recreation	0.36	0.551	1.027	0.941	1.120
Model 4						0.020	30.22	1	< 0.001
Constant	24.31	< 0.001	0.026
Age	5.14	0.023	0.979	0.961	0.997
Sexb	3.81	0.051	0.596	0.355	1.002
PSS	4.78	0.029	0.975	0.953	0.997
MOGQ social	0.04	0.834	1.005	0.962	1.049
MOGQ escapism	11.48	0.001	1.097	1.040	1.157
MOGQ competition	33.00	< 0.001	1.154	1.099	1.212
MOGQ coping	2.92	0.088	0.945	0.885	1.008
MOGQ skills	0.01	0.945	0.999	0.962	1.036
MOGQ fantasy	3.54	0.060	1.039	0.998	1.081
MOGQ recreation	0.73	0.393	1.039	0.952	1.134
BSI-18 (GSI)	30.45	< 0.001	1.026	1.016	1.035

^aχ² values refer to the increments compared to the previous restricted models. The values for the whole models are as follows: Model 2: χ² = 64.97, df = 3, p < 0.001, Nagelkerke’s R² = 0.047; Model 3: χ² = 194.89, df = 10, p < 0.001, Nagelkerke’s R² = .137; Model 4: χ² = 225.11, df = 11, p < 0.001, Nagelkerke’s R² = .157; Hosmer–Lemeshow-Test for final model p > 0.20.

^bReference Category: Men.