Table 2.

Table of multiple linear regression models with in-game performance as the dependent variable (significance shown on regression coefficients with standard error in parentheses below; *p < 0.05, **p < 0.01, ***p < 0.001).

Model	Dependent variable: performance
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Current Age	−0.049***	−0.049***		−0.043***	−0.046***	−0.047***	−0.044***	−0.034***
	(0.004)	(0.003)		(0.005)	(0.005)	(0.003)	(0.006)	(0.006)
Gender (0 = Not female, 1 = female)		−0.707***			−0.532***	−0.613***	−0.567***	−0.462***
		(0.098)			(0.118)	(0.092)	(0.109)	(0.109)
Action video game affinity (7-point Likert scale)			0.222**	0.160*	0.073
			(0.078)	(0.061)	(0.060)
Input Multitasking (z)			0.400***	0.274***	0.237***	0.235***	0.238***	-0.057
			(0.074)	(0.059)	(0.055)	(0.046)	(0.047)	(0.093)
Recent Video Game Exposure (z)			0.150*	0.082	0.041
			(0.071)	(0.056)	(0.052)
Generation (0 = older; 1 = younger)							0.149	0.445*
							(0.188)	(0.199)
Input multitasking * generation								0.408***
								(0.112)
Intercept	1.913***	2.253***	0.171*	1.758***	2.099***	2.156***	1.883***	1.251**
	(0.161)	(0.147)	(0.075)	(0.189)	(0.191)	(0.138)	(0.371)	(0.397)
Adjusted R2	0.509	0.633	0.295	0.575	0.637	0.685	0.684	0.708
F statistic	159.834*** (df = 1; 152)	133.116*** (df = 2; 151)	17.578*** (df = 3; 116)	41.271*** (df = 4; 115)	42.692*** (df = 5; 114)	111.744*** (df = 3; 150)	83.758*** (df = 4; 149)	75.147*** (df = 5; 148)

Model 1 suggests that performance and age are associated, while Model 2 suggests that there is a gender gap in performance separate from age-related variance. Models 3–6 examine which measures—both in-game and external—provide information about prior video game exposure while controlling for age and gender. Models 7–8 suggest that the relationship between multitasking input and performance is vastly different between younger and older players.

*p < 0.05; **p < 0.01; ***p < 0.001.