The effects of sport-specific training on individuals action strategies while avoiding a virtual player approaching on a 45° angle while completing a secondary task

Abstract

Sports provide varying scenarios where athletes must interact with and avoid opposing players in dynamic environments. As such, sport-specific training can improve one's ability to integrate visual information which may result in improved collision avoidance behaviours. However, improved visuomotor capabilities are highly task dependent (i.e., athletes must be tested in sport-specific settings). The current study examined whether sport-specific training influenced individuals' collision avoidance behaviours during a sport-specific task in virtual reality. Untrained young adults (N = 21, 22.9±1.9 yrs, 11 males) and specifically trained athletes (N = 18, 20±1.5 yrs, 7 males) were immersed in a virtual environment and were instructed to walk along a 7.5m path towards a goal located along the midline. Two virtual players positioned 2.83m to the left and right of the midline approached participants on a 45° angle at one of three speeds: 0.8x, 1.0x, or 1.2x each participant's average walking speed. Participants were instructed to walk to a goal without colliding with the virtual players while performing a secondary task; reporting whether a shape changed above either of the virtual players' heads. Results revealed that athletes had a higher percentage of correct responses on the secondary task compared to untrained young adults. However, there was no group differences in the average time to first avoidance or average minimum clearance, but athletes were more variable in their avoidance behaviours. Findings from this study demonstrate that athletes may be more adaptive in their behaviours and may perform better on attentionally demanding tasks in dynamic environments.

Fig 1. Experimental set-up for the (i) familiarization trials and (ii) experimental trials.

The distance between the home target and the goal was 7.5m. In the familiarization trials, one virtual player was located 2.83m to the right or left of the midline and 4m from the intersection point (blue circle). The set-up was similar for the experimental trials, with two virtual players located 2.83m to the left and right of the midline.

Fig 2. Virtual environment simulating the inside of a stadium where participants completed the task.

Fig 3

Visual representation of the calculations for the outcome variables (a) time of first avoidance and (b) minimum clearance distance.

Fig 4. Time to first avoidance (seconds; with SD bars) is a measure of the elapsed time between when the participants passed the trigger (1m) to when they initiated a behaviour change to avoid the virtual player.

This figure shows that there was no difference in the time in which an avoidance behaviour was initiated between athletes and controls (p = 890).

Fig 5. There was no influence of the direction (left or right) or speed (slow, normal, or fast) of the approaching virtual player on the average time to initiate an avoidance behaviour.

Fig 6. Time to first avoidance (seconds) is a measure of the elapsed time between when the participants passed the trigger (1m) to when they initiated a behaviour change to avoid the virtual player.

This figure shows that there was no difference in the variability of time to first avoidance between athletes and controls (p = .613).

Fig 7. The speed of the virtual player’s approach influenced the variability of time to first avoidance, such that the variability in time to first avoidance behaviour decreased from the slow, to the normal, to the fast condition.

There was no effect of the direction of the virtual player’s approach on variability in time of first avoidance.

Fig 8. Minimum clearance (meters; with SD bars) describes the minimum distance maintained between the participant and the virtual player.

This figure shows that the average minimum clearance was not significantly different between athletes and controls (p = .311).

Fig 9. The speed of the approaching virtual player influenced average minimum clearance as participants left more space in the slow condition, compared to the normal (p < .001) or fast (p < .001) speed conditions.

There was no effect of the direction of the virtual player’s approach on average minimum clearance.

Fig 10. Minimum clearance (meters) describes the minimum distance the participants maintained between them and the virtual player.

This figure shows that the variability of the minimum distance maintained by the participants was significantly different across groups, with athletes demonstrating greater variability compared to controls (p = .030).

Fig 11. Average correct responses (percentage; with SD bars) is a measure of the correct responses on the secondary task shown as a percentage of the total experimental trials completed (60 trials).

This figure shows that the athletes had a significantly higher percentage of correct responses on the secondary task compared to the controls (p = .003).