PDF(Pubmed)
Abstract：
UNASSIGNED: Unhealthy eating habits are costly and can lead to serious diseases such as obesity. Nutrition apps offer a promising approach to improving dietary behavior. Gamification elements (GEs) can motivate users to continue using nutrition apps by making them more enjoyable, which can lead to more positive behavioral changes regarding dietary choices. However, the effects of users\' preferences and individual characteristics on gamified systems are not yet understood. Current calls for research suggest that personalized gamified systems might lead to user satisfaction, continuous app use, and-ultimately-long-term improvements in diet.
UNASSIGNED: The aim was to determine the most preferred GEs in nutrition apps and to define clusters of GEs preferences in terms of personality and socio-demographic characteristics.
UNASSIGNED: We surveyed 308 people to measure their preferences regarding GEs in nutrition apps and applied best-worst scaling to determine the most preferred GEs. Furthermore, we used cluster analysis to identify different user clusters and described them in terms of personality and socio-demographic characteristics.
UNASSIGNED: We determine that GEs most favored are goals, progress bars, and coupons. We revealed three distinct user clusters in terms of personality and socio-demographic characteristics. Based on the individual factors of openness and self-perception, we find that significant differences exist between the preferences for leaderboards and coupons.
UNASSIGNED: We contribute by shedding light on differences and similarities in GE preferences relating to specific contexts and individual factors, revealing the potential for individualized nutrition apps. Our findings will benefit individuals, app designers, and public health institutions.
UNASSIGNED: The aim was to determine the most preferred GEs in nutrition apps and to define clusters of GEs preferences in terms of personality and socio-demographic characteristics.
UNASSIGNED: We surveyed 308 people to measure their preferences regarding GEs in nutrition apps and applied best-worst scaling to determine the most preferred GEs. Furthermore, we used cluster analysis to identify different user clusters and described them in terms of personality and socio-demographic characteristics.
UNASSIGNED: We determine that GEs most favored are goals, progress bars, and coupons. We revealed three distinct user clusters in terms of personality and socio-demographic characteristics. Based on the individual factors of openness and self-perception, we find that significant differences exist between the preferences for leaderboards and coupons.
UNASSIGNED: We contribute by shedding light on differences and similarities in GE preferences relating to specific contexts and individual factors, revealing the potential for individualized nutrition apps. Our findings will benefit individuals, app designers, and public health institutions.
摘要：
■不健康的饮食习惯是昂贵的，会导致严重的疾病，如肥胖。营养应用程序提供了一种有希望的方法来改善饮食行为。游戏化元素（GEs）可以激励用户继续使用营养应用程序，使其更加愉快，这可能会导致饮食选择方面更积极的行为改变。然而,用户偏好和个人特征对游戏化系统的影响尚不清楚。当前的研究呼吁表明，个性化的游戏化系统可能会导致用户满意度，连续使用应用程序，并最终长期改善饮食。
■目的是确定营养应用中最喜欢的GEs，并根据个性和社会人口统计特征定义GEs偏好的集群。
■我们调查了308人，以衡量他们在营养应用中对GEs的偏好，并应用最佳-最差比例来确定最受欢迎的GEs。此外，我们使用聚类分析来识别不同的用户聚类,并根据个性和社会人口统计特征对其进行描述.
■我们确定GEs最受欢迎的是目标，进度条,和优惠券。我们在个性和社会人口统计学特征方面揭示了三个不同的用户集群。基于开放性和自我感知的个体因素，我们发现，排行榜和优惠券的偏好存在显著差异。
■我们通过阐明与特定环境和个体因素相关的GE偏好的差异和相似性做出贡献，揭示个性化营养应用程序的潜力。我们的发现将使个人受益，应用程序设计师，和公共卫生机构。
■目的是确定营养应用中最喜欢的GEs，并根据个性和社会人口统计特征定义GEs偏好的集群。
■我们调查了308人，以衡量他们在营养应用中对GEs的偏好，并应用最佳-最差比例来确定最受欢迎的GEs。此外，我们使用聚类分析来识别不同的用户聚类,并根据个性和社会人口统计特征对其进行描述.
■我们确定GEs最受欢迎的是目标，进度条,和优惠券。我们在个性和社会人口统计学特征方面揭示了三个不同的用户集群。基于开放性和自我感知的个体因素，我们发现，排行榜和优惠券的偏好存在显著差异。
■我们通过阐明与特定环境和个体因素相关的GE偏好的差异和相似性做出贡献，揭示个性化营养应用程序的潜力。我们的发现将使个人受益，应用程序设计师，和公共卫生机构。
