AUTHOR=Capio Catherine M. , Tsang William W. N. , Yam Timothy T. T. , Uiga Liis , Wong Thomson W. L. , Masters Rich S. W. 

TITLE=An examination of the cognitive and affective processes in errorless motor learning: study protocol

JOURNAL=Frontiers in Psychology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2025.1685720

DOI=10.3389/fpsyg.2025.1685720

ISSN=1664-1078

ABSTRACT=Acquiring movement skills is crucial across the lifespan, supporting an individual’s participation in sports and physical activities. Errorless motor learning, which promotes success during practice, has been shown to be effective for acquiring or reacquiring (e.g., following injury/disease) movement skills. This research explores the underlying processes of errorless motor learning in children and older adults. We will investigate two distinct processes associated with motor learning: (i) cognitive processing measured by movement variability and prefrontal cortex (PFC) activity and (ii) affective processing measured by perceived competence. We will recruit two participant groups—children, and older adults—who will practice a novel throwing task in either a condition where errors are minimized or a condition where errors freely occur. We will measure task performance, movement variability, perceived competence, and PFC activity before, during, and after practice. We will control for individual cognitive abilities (processing speed and executive function) and use hierarchical linear mixed models to compare the variables between the practice conditions and to verify whether the cognitive and affective processes influence outcomes following practice. The findings are expected to contribute to our understanding of skills acquisition across the lifespan and help facilitate the (re)acquisition of motor skills by children and older adults through programs provided by physiotherapists, coaches, teachers, and health professionals. This study has been registered in the Open Science Framework Registries (https://doi.org/10.17605/OSF.IO/YTERV).