共同设计用于数字暴饮暴食干预的预测数据可视化
Adrian Ortega1,2, Isabel R Rooper1,3, Thomas Massion1,3
1Center for Behavioral Intervention Technologies, Northwestern University Feinberg School of Medicine, 750 N. Lake Shore Dr., 10th Floor, Chicago, IL 60611, USA.
Translational behavioral medicine
|April 1, 2025
概括
用户希望数字健康工具显示行为变化的预测,但更喜欢简单,鼓励设计,尊重自治. 这些见解可以改善数字干预参与度.
科学领域:
- 数字健康干预措施 数字健康干预措施
- 行为科学是一种行为科学.
- 人与计算机的互动.
背景情况:
- 数字干预可以预测用户的健康行为,以帮助改变.
- 呈现预测不确定性和可操作的见解带来了设计挑战.
研究的目的:
- 共同设计会议探讨了用户参与数字暴饮暴食干预中的预测数据.
- 研究了预测间隔和进度可视化如何影响用户的感知.
主要方法:
- 采访了22名经常性暴饮暴食和肥胖的成年人.
- 展示了5种行为改变策略的预测显示的原型.
- 对用户对预测数据呈现和不确定性的反进行主题分析.
主要成果:
- 用户欢迎预测数据,但优先考虑自主性和尽量减少负面情绪.
- 喜欢简单,有组织的设计,以便快速比较策略预测.
- 渴望得到鼓励和灵活性,如果预测没有满足.
结论:
- 数字干预应以清晰而鼓舞人心的方式呈现预测.
- 设计应该支持用户的自主权,并管理预期.
- 建议在实践中进行经验验证.
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