Self-modelled versus skilled-peer modelled AO+MI effects on skilled sensorimotor performance_McNeill et al.

Published: 01-11-2020| Version 1 | DOI: 10.17632/xk68tw3kx6.1
Contributors:
Eoghan McNeill,
Adam Toth,
Niall Ramsbottom,
Mark Campbell

Description

Data set represents processed data and associated output files for stage 2 registered report investigated the effect of two separate Action Observation+Motor Imagery (AO+MI) conditions on golf putting performance in a sample of skilled golfers, link to accepted stage 1 report published in the Psychology of Sport and Exercise here https://doi.org/10.1016/j.psychsport.2020.101683. Purpose of the study was to examine whether a self-modelled AO+MI condition would prove to be more effective than a peer-skilled-model AO+MI condition. Results demonstrate that both groups improve putting accuracy and precision significantly from baseline-post test (MRE_MEAN_OUTLIERSREMOVED and BVE variables) No significant differences between groups for putting accuracy or consistency. However significant difference between groups at post-test for club-path (direction, DIRECT variable) when baseline performance is controlled for as a covariate, with the self-modelled AO+MI condition demonstrating a club path that was significantly closer to zero degrees (indicative of better performance) that the AO+MI peer-skill-model condition. Based on these finding self-modelling may be a more effective method of implementing AO+MI conditions in skilled performers, but only for measures of performance which are easily observed in the observation video. Data included here is the processed data set upon which the analyses were conducted. Output files of analyses, and the experimental stimuli used for the peer-skilled-model condition.

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