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Measuring Engagement of Spectators of Social Digital Games
Published on: July 3, 2021
Playful sport design and sport engagement: A diary study among amateur athletes
Juriena D de Vries1, Yuri S Scharp2, Arnold B Bakker3
1Department of Health, Medical, and Neuropsychology, Leiden University, the Netherlands.
Abstract:
Sport engagement is essential for athletes' performance and long-term commitment. Drawing on self-regulation and play literature, we propose that athletes can proactively enhance their sport engagement and, indirectly, performance (i.e., goal progression) by enacting Playful Sport Design (PSD). PSD involves proactively adding play elements to training by "designing fun" (DF; incorporating creativity, humor, and fantasy) and "designing competition" (DC; fostering self-imposed challenges, keeping score, and driving self-improvement). Additionally, we explored how PSD's effectiveness varies across different sports settings: solitary versus group training and coached versus non-coached sessions. To investigate this, athletes who trained at least twice a week participated in a four-week weekly diary study using reconstruction methodology (N = 99 individuals, n = 616 sport activities). The sample consisted mostly of amateur athletes (88 %), with an average age of 28.4 years (65 % women, 35 % men). Strength sports was the most common sport (33 %), followed by fitness (19.2 %), athletics (16.2 %), and ball sports (7.1 %). On average, they trained 3.7 times per week and had 14.2 years of experience. Supporting our hypotheses, multilevel regression analyses revealed that DF and DC both enhanced goal progression through increased engagement. Notably, DF was more effective in group settings than in solitary sessions, whereas DC was more effective in either the presence of a coach (vs. no coach) or in solitary settings (vs. group settings). The findings demonstrate that athletes can initiate play to drive their own engagement and goal progression, as well as highlight the sports environments in which this behavior is most effective.
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