Abstract
BackgroundGamification and persuasive games are effective tools to motivate behavior change, particularly to promote daily physical activities. On the one hand, studies have suggested that a one-size-fits-all approach does not work well for persuasive game design. On the other hand, player modeling and recommender systems are increasingly used for personalizing content. However, there are few existing studies on how to build comprehensive player models for personalizing gamified systems, recommending daily physical activities, or the long-term effectiveness of such gamified exercise-promoting systems.ObjectiveThis paper aims to introduce a gamified, 24/7 fitness assistant system that provides personalized recommendations and generates gamified content targeted at individual users to bridge the aforementioned gaps. This research aims to investigate how to design gamified physical activity interventions to achieve long-term engagement.MethodsWe proposed a comprehensive model for gamified fitness recommender systems that uses detailed and dynamic player modeling and wearable-based tracking to provide personalized game features and activity recommendations. Data were collected from 40 participants (23 men and 17 women) who participated in a long-term investigation on the effectiveness of our recommender system that gradually establishes and updates an individual player model (for each unique user) over a period of 60 days.ResultsOur results showed the feasibility and effectiveness of the proposed system, particularly for generating personalized exercise recommendations using player modeling. There was a statistically significant difference among the 3 groups (full, personalized, and gamified) for overall motivation (F3,36=22.49; P<.001), satisfaction (F3,36=22.12; P<.001), and preference (F3,36=15.0; P<.001), suggesting that both gamification and personalization have positive effects on the levels of motivation, satisfaction, and preference. Furthermore, qualitative results revealed that a customized storyline was the most requested feature, followed by a multiplayer mode, more quality recommendations, a feature for setting and tracking fitness goals, and more location-based features.ConclusionsOn the basis of these results and drawing from the gamer modeling literature, we conclude that personalizing recommendations using player modeling and gamification can improve participants’ engagement and motivation toward fitness activities over time.
Highlights
A sedentary lifestyle is defined as a lifestyle in which an individual does not receive regular amounts of physical activity, which is becoming a significant public health issue [1]
To address these research gaps, we propose a comprehensive model for gamified fitness recommender systems that use detailed and dynamic player modeling and wearable-based tracking to provide personalized game features and activity recommendations
Our work includes the following major contributions to the field of fitness recommenders and exergames: 1. We offer a conceptual model and system architecture for personalized gamified activity recommendations using a combination of player modeling, gamifications, and activity tracking
Summary
A sedentary lifestyle is defined as a lifestyle in which an individual does not receive regular amounts of physical activity, which is becoming a significant public health issue [1]. The popularity of computer games and their engaging nature has created a strong trend to use games for nonentertainment purposes [5] This trend includes overlapping topics and terms such as gamification (the use of game features and mechanics in nongame applications [6]), serious games (aimed primarily at being an educational yet entertaining tool [7]), persuasive games (games for promoting behavior change [8]), and exergames (a combination of physical exercise with games [9]). There are few existing studies on how to build comprehensive player models for personalizing gamified systems, recommending daily physical activities, or the long-term effectiveness of such gamified exercise-promoting systems. Methods: We proposed a comprehensive model for gamified fitness recommender systems that uses detailed and dynamic player modeling and wearable-based tracking to provide personalized game features and activity recommendations. Conclusions: On the basis of these results and drawing from the gamer modeling literature, we conclude that personalizing recommendations using player modeling and gamification can improve participants’ engagement and motivation toward fitness activities over time
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