Motor performance under OPTIMAL conditions: comparing task-relevant and task-irrelevant autonomy support
DOI:
https://doi.org/10.47197/retos.v79.118599Keywords:
Motor behavior, Volleyball, Bayesian statistics, Sport psychology, AdolescentsAbstract
Introduction: The OPTIMAL Theory proposes that enhanced expectancies for performance, autonomy support, and external focus of attention act as interacting pillars that facilitate motor skill performance. However, evidence for their benefits in sport-specific motor skills remains inconsistent.
Objective: Evaluate the effects of the interactive OPTIMAL pillars on the performance of a volleyball skill by manipulating autonomy over task-relevant and task-irrelevant aspects.
Methodology: Eighteen adolescents with volleyball practice experience performed a volleyball attacking skill aimed at striking the center of a target under three different conditions: (1) an OPTIMAL condition (which includes reception of positive feedback and instruction inducing external focus of attention) plus a task-irrelevant choice (selection of the ball); (2) an OPTIMAL condition plus a task-relevant choice (whether to receive a demonstration of the motor execution); and (3) a control condition. Each participant completed 10 trials per condition across three sessions separated by seven days. The control condition was completed on the first day, and the two OPTIMAL conditions were counterbalanced on days two and three. Performance on attack accuracy was assessed using a score ranging from 0 to 3 points. Differences between conditions were analyzed using Bayesian repeated-measures one-way ANOVA.
Results and Conclusions: No significant differences were found in attack accuracy across the different conditions. These findings suggest that, in participants with task experience, implementing the OPTIMAL theory pillars plus task-relevant or task-irrelevant choice did not enhance volleyball attacking skill performance relative to the control condition.
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Copyright (c) 2026 João El Rei Pires de Araújo Júnior, Fabian Alberto Romero Clavijo, Lorenzo Iop Laporta, Gabriela Machado Ribeiro, Ricardo Drews
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