Table 3.

The best fitting linear models with each EPELI measure as the dependent variable and age, gender, gaming background, familiarity of the tasks, and the type of HMD as independent variables

Dependent variable	Independent variable	Estimate (β)	SD	t	p	△AIC	R2	Adj. R2
Total score	(Intercept)	21.253	8.166	2.60	0.011*	− 3.77	0.192	0.159
	Gender	4.524	1.615	2.80	0.007**
	Age (years)	2.326	0.700	3.33	0.001**
	Gaming background	4.272	2.344	1.82	0.072
Task efficacy	(Intercept)	0.138	0.153	0.90	0.371	− 3.04	0.185	0.151
	Gender	0.099	0.029	3.34	0.001**
	Age (years)	0.024	0.013	1.77	0.082
	HMD	− 0.051	0.030	− 1.74	0.085
Navigation efficacy	(Intercept)	0.010	0.021	0.46	0.645	− 2.97	0.220	0.199
	Gender	0.014	0.004	3.35	0.001***
	Age (years)	0.006	0.002	3.25	0.002**
Controller motion	(Intercept)	92,835	18,483	5.02	< 0.001***	− 5.33	0.073	0.048
	Gender	− 7095	3580	− 1.98	0.051
	Age (years)	− 2664	1685	− 1.58	0.118
Total actions	(Intercept)	836.820	157.34	5.32	< 0.001***	− 5.01	0.137	0.114
	Gender	− 85.100	30.480	− 2.79	0.007**
	Age (years)	− 32.570	14.340	− 2.27	0.026*
TBPM	(Intercept)	− 3.586	2.921	− 1.23	0.223	− 2.16	0.130	0.107
	Age (years)	0.787	0.266	2.95	0.004**
	Gender	1.038	0.566	1.83	0.070
Clock checks	(Intercept)	34.696	1.919	18.08	< 0.001***	− 3.02	0.055	0.042
	Gender	− 6.309	3.025	− 2.09	0.040*
EBPM	(Intercept)	3.870	0.118	32.79	< 0.001***	− 6.42	0.039	0.026
	Gender	0.324	0.186	1.74	0.086

N = 77

*** p < 0.001, ** p < 0.01, * p < 0.05

For gender, girl = 1 and boy = 0. Age in years. For gaming background, regular gaming = 1, no regular gaming = 0. For HMD, Pico Neo 2 Eye = 1, Oculus GO = 0. △AIC, change in the Akaike Information Criterion from the full model