. 2021 Sep 20;11:18584. doi: 10.1038/s41598-021-98146-x

Table 1.

Analysis of variance results and summary of post hocs for the effects of intervention on of reading, eye movements and magnocellular tasks.

	Time × intervention	Simple effects for time		Simple effects for intervention
Reading accuracy	Sig. Wilk’s λ = .83, F(2, 60) = 6.00, p = .004, η_p² = 0.17	Comparison (T1 = T2) AVG+ (T1 < T2) AVG-R (T1 < T2)	T1: p = .160, η_p² = 0.06 T2: p = .001, η_p² = 0.21	T1: Comparison = AVG+ = AVG-R T2: Comparison ≠ AVG+ or AVG-R; AVG+ = AVG-R
Reading rate	Sig. Wilk’s λ = .74, F(2, 60) = 10.79, p < .001, η_p² = 0.27	Comparison (T1 = T2) AVG+ (T1 < T2) AVG-R (T1 < T2)	T1: p = .893, η_p² = 0.04 T2: p = .048, η_p² = 0.09	T1: Comparison = AVG+ = AVG-R T2: Comparison ≠ AVG+ or AVG-R; AVG+ = AVG-R
Reading comprehension	Sig. Wilk’s λ = .79, F(2, 60) = 7.91, p = .001, η_p² = 0.21	Comparison (T1 = T2) AVG+ (T1 < T2) AVG-R (T1 < T2)	T1: p = .444, η_p² = 0.03 T2: p < .001, η_p² = 0.25	T1: Comparison = AVG+ = AVG-R T2: Comparison ≠ AVG+ or AVG-R; AVG+ = AVG-R
Rapid naming	Sig. Wilk’s λ = .81, F(2, 60) = 6.95, p = .002, η_p² = 0.19	Comparison (T1 = T2) AVG+ (T1 < T2) AVG-R (T1 < T2)	T1: p = .622, η_p² = 0.02 T2: p = .035, η_p² = 0.11	T1: Comparison = AVG+ = AVG-R T2: Comparison ≠ AVG+ or AVG-R; AVG+ = AVG-R
Fixation duration	NS Wilk’s λ = .99, F(2, 60) = 0.03, p = .971, η_p² = 0.01	Comparison (T1 = T2) AVG+ (T1 = T2) AVG-R (T1 = T2)	T1: p = .668, η_p² = 0.01 T2: p = .727, η_p² = 0.01	T1: Comparison = AVG+ = AVG-R T2: Comparison = AVG+ = AVG-R
Fixation count	NS Wilk’s λ = .98, F(2, 60) = 0.45, p = .641, η_p² = 0.02	Comparison (T1 = T2) AVG+ (T1 > T2) AVG-R (T1 > T2)	T1: p = .816, η_p² = 0.01 T2: p = .184, η_p² = 0.06	T1: Comparison = AVG+ = AVG-R T2: Comparison = AVG+ = AVG-R
Regression count	NS Wilk’s λ = .97, F(2, 60) = 0.81, p = .449, η_p² = 0.03	Comparison (T1 = T2) AVG+ (T1 = T2) AVG-R (T1 > T2)	T1: p = .539, η_p² = 0.02 T2: p = .092, η_p² = 0.08	T1: Comparison = AVG+ = AVG-R T2: Comparison = AVG+ = AVG-R
Flicker fusion 5%	NS Wilk’s λ = .99, F(2, 60) = .14, p = .872, η_p² = .01	Comparison (T1 = T2) AVG+ (T1 = T2) AVG-R (T1 = T2)	T1: p = .748, η_p² = 0.01 T2: p = .686, η_p² = 0.01	T1: Comparison = AVG+ = AVG-R T2: Comparison = AVG+ = AVG-R
Flicker fusion 75%	NS Wilk’s λ = .92, F(2, 60) = 2.78, p = .070, η_p² = .09	Comparison (T1 = T2) AVG+ (T1 < T2) AVG-R (T1 = T2)	T1: p = .251, η_p² = 0.05 T2: p = .564, η_p² = 0.02	T1: Comparison = AVG+ = AVG-R T2: Comparison = AVG+ = AVG-R

Time × intervention

Simple effects for time

Simple effects for intervention

Reading accuracy

Sig. Wilk’s λ = .83, F(2, 60) = 6.00, p = .004, η_p² = 0.17

Comparison (T1 = T2)

AVG+ (T1 < T2)

AVG-R (T1 < T2)

T1: p = .160, η_p² = 0.06

T2: p = .001, η_p² = 0.21

T1: Comparison = AVG+ = AVG-R

T2: Comparison ≠ AVG+ or AVG-R;

AVG+ = AVG-R

Reading rate

Sig. Wilk’s λ = .74, F(2, 60) = 10.79, p < .001, η_p² = 0.27

Comparison (T1 = T2)

AVG+ (T1 < T2)

AVG-R (T1 < T2)

T1: p = .893, η_p² = 0.04

T2: p = .048, η_p² = 0.09

T1: Comparison = AVG+ = AVG-R

T2: Comparison ≠ AVG+ or AVG-R;

AVG+ = AVG-R

Reading comprehension

Sig. Wilk’s λ = .79, F(2, 60) = 7.91, p = .001, η_p² = 0.21

Comparison (T1 = T2)

AVG+ (T1 < T2)

AVG-R (T1 < T2)

T1: p = .444, η_p² = 0.03

T2: p < .001, η_p² = 0.25

T1: Comparison = AVG+ = AVG-R

T2: Comparison ≠ AVG+ or AVG-R;

AVG+ = AVG-R

Rapid naming

Sig. Wilk’s λ = .81, F(2, 60) = 6.95, p = .002, η_p² = 0.19

Comparison (T1 = T2)

AVG+ (T1 < T2)

AVG-R (T1 < T2)

T1: p = .622, η_p² = 0.02

T2: p = .035, η_p² = 0.11

T1: Comparison = AVG+ = AVG-R

T2: Comparison ≠ AVG+ or AVG-R;

AVG+ = AVG-R

Fixation duration

NS Wilk’s λ = .99, F(2, 60) = 0.03, p = .971, η_p² = 0.01

Comparison (T1 = T2)

AVG+ (T1 = T2)

AVG-R (T1 = T2)

T1: p = .668, η_p² = 0.01

T2: p = .727, η_p² = 0.01

T1: Comparison = AVG+ = AVG-R

T2: Comparison = AVG+ = AVG-R

Fixation count

NS Wilk’s λ = .98, F(2, 60) = 0.45, p = .641, η_p² = 0.02

Comparison (T1 = T2)

AVG+ (T1 > T2)

AVG-R (T1 > T2)

T1: p = .816, η_p² = 0.01

T2: p = .184, η_p² = 0.06

T1: Comparison = AVG+ = AVG-R

T2: Comparison = AVG+ = AVG-R

Regression count

NS Wilk’s λ = .97, F(2, 60) = 0.81, p = .449, η_p² = 0.03

Comparison (T1 = T2)

AVG+ (T1 = T2)

AVG-R (T1 > T2)

T1: p = .539, η_p² = 0.02

T2: p = .092, η_p² = 0.08

T1: Comparison = AVG+ = AVG-R

T2: Comparison = AVG+ = AVG-R

Flicker fusion 5%

NS Wilk’s λ = .99, F(2, 60) = .14, p = .872, η_p² = .01

Comparison (T1 = T2)

AVG+ (T1 = T2)

AVG-R (T1 = T2)

T1: p = .748, η_p² = 0.01

T2: p = .686, η_p² = 0.01

T1: Comparison = AVG+ = AVG-R

T2: Comparison = AVG+ = AVG-R

Flicker fusion 75%

NS Wilk’s λ = .92, F(2, 60) = 2.78, p = .070, η_p² = .09

Comparison (T1 = T2)

AVG+ (T1 < T2)

AVG-R (T1 = T2)

T1: p = .251, η_p² = 0.05

T2: p = .564, η_p² = 0.02

T1: Comparison = AVG+ = AVG-R

T2: Comparison = AVG+ = AVG-R

Sig = significant; NS = Non-significant; AVG-R = Action Video Game-Regular Group; AVG + = Increased Attention Action Video Game Group; Comparison = Comparison Group.