Table Tennis for Health: A Multidimensional Perspective on Its Physical, Emotional, and Social Advantages

Abstract

Background/Objectives: Table tennis is commonly perceived as a recreational or competitive sport; however, growing evidence highlights its potential as a multidimensional tool for health promotion. This study investigates the perceived physical, cognitive, emotional, and social benefits of regular table tennis practice, emphasizing its contribution to health beyond the purely sporting dimension. Methods: A mixed-method design with a predominantly quantitative approach was employed. A structured questionnaire was administered to 329 table tennis players in Catalonia. Descriptive statistics, exploratory factor analysis (EFA), multiple linear regression, Pearson correlations, and hierarchical cluster analysis (Ward’s method) were conducted to examine perceived benefits and identify user profiles. Factor analysis revealed two dimensions: physical–cognitive and emotional–social benefits. Results: The EFA produced a robust two-factor structure, explaining 76.6% of the variance (KMO = 0.941; Bartlett’s test, p < 0.001). Both dimensions showed excellent internal consistency (Cronbach’s α > 0.91). Regression analysis demonstrated that both factors significantly predicted the overall perception of table tennis as a health-enhancing activity (R2 = 0.199), with physical–cognitive benefits exerting the strongest effect (β = 0.375; p < 0.001). Cluster analysis identified three distinct profiles: Skeptical, Functional, and Integrative—with significant differences in perceived benefits (η 2 = 0.710 for the emotional– social factor). Conclusions: Table tennis emerges as an inclusive, low-impact activity with strong potential to foster physical, emotional, and social well-being. Its accessibility and adaptability make it appropriate for diverse populations. These findings support its inclusion in public health strategies and community programs promoting holistic wellness. Future research should further explore motivational drivers across profiles and extend analyses to underrepresented populations.