Impact of focus of attention on aiming performance in the first-person shooter videogame Aim Lab
Date
25/07/2023Metadata
Show full item recordAbstract
Research examining the impact of Focus of Attention (FoA) has consistently demonstrated a benefit of adopting an external FoA over an internal FoA across a variety of sports and other domains. However, FoA research has yet to be applied within the rapidly growing world of competitive gaming. This study investigated whether an external FoA provided benefits over an internal FoA for aiming performance in First-Person Shooter (FPS) videogames, using the aim-training game Aim Lab. The study explored whether the level of participants’ previous experience of FPS games impacted any effect, as few studies have investigated this directly. Participants with high (N=20) and low (N=17) FPS experience who had a minimum of 200 hours FPS experience were selected for the study. The participants were instructed before each set of ten trials to either attend to their wrist/arm movements (internal FoA) or to the target (external FoA). There was no significant main effect of FoA on performance and no significant interaction between FoA and experience. In contrast to findings in other studies, an external FoA provided no performance benefits over an internal FoA in the FPS game Aim Lab. We discuss methodological issues related to the measures used and suggest avenues for future research with a view to improving understanding of putative underlying mechanisms for FoA effects.
Citation
Lamers James , R & O'Connor , A R 2023 , ' Impact of focus of attention on aiming performance in the first-person shooter videogame Aim Lab ' , PLoS One , vol. 18 , no. 7 , e0288937 . https://doi.org/10.1371/journal.pone.0288937
Publication
PLoS One
Status
Peer reviewed
ISSN
1932-6203Type
Journal article
Description
Funding: The authors received funding of £300 from the University of St Andrews-School of Psychology and Neuroscience which is awarded to all Psychology BSc students to complete dissertation research.Collections
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