The association between visual attention and body movement-controlled video games, balance and mobility in older adults

Table 4 Forward stepwise multiple linear regression for balance measures with visual attention and other variables. The variables that were entered into each model are shown beneath. The model for OLST was run first with the full range of variables (full model), and secondly excluding the non-modifiable factors of age and gender

Dependent Variable	Predictor variable	R² at each step	Co-efficient B	Standardized Coefficient	t	P value
OLST (full model)¹	Age Cumulative path-length Step length variability	0.283 0.408 0.460	− 0.032 − 0.979 − 0.78	−0.347 − 0.299 − 0.253	−3.727 −3.144 − 2.144	0.005 0.018 0.040
¹predictors entered into the analysis: UFV-D, stride length variability, Cumulative path-length, VA, gender, age, no. medications, general health, and MoCA R² for the model = 0.46, F = 13.01 p for the model < 0.001
OLST (excluding age and gender) ²	Cumulative path-length Step length variability	0.267 0.359	−1.284 −1.015	−0.392 − 0.328	−3.107 − 2.597	0.000 0.013
²predictors entered into the analysis: UFV-D, stride length variability, Cumulative path-length, VA, no. medications, general health, and MoCA R² for the model = 0.36, F = 13.17 p for the model < 0.001
Cumulative pathlength³	OLST Vel/leg	0.267 0.343	−0.12 − 0.50	−0.517 − 0.3	−4.183 − 2.322	0.004 0.025
³predictors entered into the analysis: UFV-D, Vel/Leg, OLST, VA, gender, age, no. medications, general health and MoCA R² for the model = 0.343, F = 12.25 p for the model < 0.001

MoCA the Montreal Cognitive Assessment, UFV-D the Useful Field of View test- Dynamic, VA Visual Acuity, OLST One-Legged Stance Test, Vel/Leg Velocity/Leg length

ISSN: 1471-2318