The Effect of Twisted Salto Backwards Self-modelling on Mental Rotation Task Performance in Parkour Athletes: a Pilot Study
Year: 2026
Type: article
Study design: Clinical Trial
Abstract: The purpose of this study was to examine the effects of self-modelling of twisted salto backward movements on mental rotation performance in parkour athletes. Twenty trained athletes participated in three testing sessions: a baseline assessment, an immediate evaluation after a single self-modelling session, and a follow-up after a three-week training period including 12 self-modelling sessions. Participants performed a mental body rotation task including three rotation angles (135°, 180°, and 225°). Results indicated that self-modelling led to immediate improvements in accuracy and long-term enhancements in both speed and accuracy of mental rotation. The greatest improvements were observed at the 135° and 225° angles, suggesting that repeated exposure to self-modelling may enhance mental rotation performance, a key cognitive component underlying perceptual–motor processes in acrobatic skills. These findings support the idea that self-modelling facilitates the refinement of egocentric motor representations, improving spatial cognition and potentially supporting anticipatory motor planning. In conclusion, repeated self-modelling sessions (12 training exposures) represent an effective and low-cost method to enhance mental rotation abilities in complex acrobatic tasks. Integrating structured self-modelling into acrobatic training programs may support improvements in mental rotation abilities, which are important for tasks requiring advanced spatial orientation and could potentially contribute to skill acquisition and movement precision in high-risk movements. Future research should examine whether these cognitive improvements translate to enhanced motor performance and reduced execution errors in acrobatic skills.
Source: Science of Gymnastics Journal
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7225076121