VR Tennis Training Effects on Psychological Outcomes

Psychological Adaptation, Sports Performance

Virtual Reality, Tennis, Flow Experience, Embodied Cognition, Technology Acceptance, Sports Psychology, Self-Efficacy

This randomized controlled trial examined the effects of an 8-week virtual reality (VR) tennis training intervention on psychological outcomes among Chinese university tennis players. A total of 180 participants were randomly assigned to either a VR training group (n=90) using Meta Quest 2 headsets or a traditional training control group (n=90). The VR group received immersive tennis training twice weekly for 60 minutes per session, while the control group received equivalent traditional coaching. Primary outcomes included self-efficacy, flow experience, embodied cognition, and intention to use, measured at baseline and post-intervention. Secondary analyses examined whether self-efficacy and flow experience mediated the relationship between VR training and intention to use. The study aimed to provide evidence for the effectiveness of VR technology in sports training and to elucidate the psychological mechanisms underlying VR training benefits.

Background: Virtual reality (VR) technology has emerged as a promising tool for sports training, offering immersive environments that simulate real-world athletic scenarios. Tennis represents an ideal sport for VR training applications due to its technical complexity, spatial demands, and the importance of anticipatory skills. Despite growing adoption of VR in sports contexts, the psychological mechanisms underlying VR training effectiveness remain insufficiently understood. Theoretical Framework: This study was grounded in four theoretical perspectives: (1) Bandura's Self-Efficacy Theory, proposing that VR training enhances confidence through mastery experiences; (2) Csikszentmihalyi's Flow Theory, suggesting VR environments facilitate optimal psychological states; (3) Embodied Cognition Theory, emphasizing that cognitive processes are rooted in bodily interactions; and (4) the Technology Acceptance Model, providing a framework for understanding intention to use technology. Objectives: Primary objectives were to determine whether VR tennis training produces greater improvements in self-efficacy, flow experience, embodied cognition, and intention to use compared to traditional training. Secondary objectives investigated whether self-efficacy and flow experience mediate the effect of VR training on intention to use. Methods: A parallel-group, single-blind randomized controlled trial was conducted at Hezhou University, Guangxi, China. Eligible participants were undergraduate students aged 18-26 years enrolled in Physical Education or Sports Science programs with at least two semesters of tennis instruction. Participants were randomly assigned using computer-generated random numbers with stratification by sex and year of study. Intervention: The VR group received 8 weeks of immersive tennis training using Meta Quest 2 head-mounted displays (2 sessions/week, 60 minutes/session, 16 sessions total). Training included warm-up in virtual environment (10 min), technical skill practice (25 min), tactical decision-making scenarios (20 min), and cool-down (5 min). The control group received matched traditional tennis training with the same frequency, duration, and content structure. Outcome Measures: Self-efficacy was measured using an 8-item scale adapted from Bandura (2006). Flow experience was assessed using a 10-item scale based on Csikszentmihalyi (1990). Embodied cognition was measured using an 8-item scale adapted from presence questionnaires. Intention to use was assessed with a 6-item scale adapted from the Technology Acceptance Model. Sport motivation (SMS-II) was measured as a covariate. Statistical Analysis: Between-group differences were examined using analysis of covariance (ANCOVA) controlling for baseline scores and sport motivation. Effect sizes were calculated as Hedges' g. Parallel mediation analysis was conducted using the PROCESS macro with bias-corrected bootstrap confidence intervals (10,000 samples).

China