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基于智能手表的定制游戏化和用户建模以激励体育炼:使用最大差异缩放细分方法进行实验研究.

Jie Yao1, Di Song1, Tao Xiao2

  • 1School of Economics and Management, Harbin Institute of Technology (Shenzhen), Shenzhen, China.

JMIR serious games
|March 11, 2025
PubMed
概括

定制的智能手表游戏化,使用最大差异缩放 (MaxDiff),识别不同的用户部分,以更好地激励身体炼. 这种方法超越了为改善健康行为改变而设计的一种适合所有人的设计.

关键词:
马克斯·迪夫·迪夫 (MaxDiffDiff) 是一个最大的差异缩放规模.身体炼就是体力炼.智能手表 智能手表量身定制的游戏化用户细分化用户细分化

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科学领域:

  • 人与计算机的交互
  • 行为科学 行为科学
  • 数字健康数字健康

背景情况:

  • 智能手表游戏化显示了健身应用程序的潜力,但由于设计统一,缺乏确的证据.
  • 用户偏好和需求的个体差异对于有效的游戏化至关重要,但往往被忽视.
  • 针对定制游戏化的现有用户建模面临着传统评级表和相关性分析的局限性.

研究的目的:

  • 通过开发创新的用户建模方法来增强基于智能手表的游戏化,以定制体育炼动机.
  • 将个人偏好和对游戏元素的需求纳入用户细分,使用最大差异缩放 (MaxDiff) 技术.
  • 通过使用MaxDiff来克服传统方法的局限性,以实现更准确的用户细分和定制的游戏化解决方案.

主要方法:

  • 对378名智能手表用户进行了两次MaxDiff实验,分析了16个游戏元素的偏好和动机驱动因素.
  • 利用隐性类统计模型,根据用户对游戏化元素的反应来识别不同的用户部分.
  • 开发了预测模型,以快速将未来的用户分类到适当的细分市场,以实现个性化的游戏化.

主要成果:

  • 根据对游戏化元素的偏好,确定了三个不同的用户部分.
  • 发现了四个动机部分:目标,沉浸式体验,奖励和社会比较,突出了用户的异质性.
  • 观察到基于偏好和基于动机的部分之间存在显著差异,这表明享受和激励影响之间存在差距.

结论:

  • 这项研究开创了基于MaxDiff的用户细分,用于定制智能手表游戏化,以促进体育炼.
  • 详细了解游戏元素的偏好和在各种智能手表用户领域的有效性.
  • 支持MaxDiff实验作为对调查的优越替代方案,以捕捉医疗应用中的用户异质性.