Athletes’ mental fatigue: development and validation of a scale and application for assessing mental fatigue in athletes
DOI:
https://doi.org/10.47197/retos.v78.118870Keywords:
Athletes visual analog scale, application, athletes' mental fatigue, psychometric validationAbstract
Introduction: Mental fatigue can impair athletes’ cognitive performance, emotional regulation, decision-making, and physical performance during training and competition. Therefore, reliable tools are needed to assess it effectively. Although the Visual Analog Scale (VAS) is widely used for subjective assessment, a multi-item VAS specifically designed for athletes and integrated with a digital application remains limited.
Objective: This study aimed to develop and validate a multi-item Visual Analog Scale (VAS) for assessing mental fatigue in athletes and to develop and evaluate a mental fatigue assessment application.
Methodology: This research consisted of three phases. Phase 1 developed a 20-item VAS covering four components: cognitive and mental function, emotional function, behavioral function, and physical and physiological responses, with reliability tested using Cronbach’s alpha. Phase 2 developed a mental fatigue assessment application including login, assessment, results with management guidelines, history records, and logout, and evaluated reliability and user satisfaction. Phase 3 assessed application suitability by three information technology experts.
Results: Cronbach’s alpha coefficients ranged from .76 to .83 across components, with an overall reliability of .90. The application showed reliability of .862 and the highest level of user satisfaction. Experts rated the application’s overall suitability at a high level.
Discussion: The findings indicate that the developed VAS and application provide a reliable and practical tool for assessing athletes’ mental fatigue and supporting monitoring during training and competition.
Conclusions: The developed scale and application demonstrated acceptable reliability and usability. Future studies should conduct confirmatory factor analysis with larger samples.
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