开发儿童新型饮食评估工具的用户要求:混合方法研究
Zoë van der Heijden1, Femke de Gooijer1, Guido Camps1
1Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, Netherlands.
JMIR formative research
|February 1, 2024
概括
5-6岁的儿童可以协助收集饮食数据,提高个性化营养的准确性. 未来的工具应该包含儿童友好的设计,提示和自主性,以提高可用性和参与度.
科学领域:
- 儿童营养学 儿童营养学
- 人与计算机的交互
- 行为科学 行为科学
背景情况:
- 儿童肥胖及其伴随疾病正在增加,需要有效的饮食干预措施.
- 目前的饮食干预措施显示长期效果不令人满意,推动了对个性化方法的需求.
- 准确的饮食摄入数据对于个性化营养至关重要,儿童可能有助于数据收集.
研究的目的:
- 确定用户对适合5至6岁儿童的饮食评估工具的需求.
- 探索以儿童为中心的,探索性的顺序混合方法方法来开发工具.
主要方法:
- 文献研究提供了初始用户需求和原型创意的信息.
- 开发了三个原型 (FoodBear,myBear,FoodCam) 并与14名儿童 (5-6岁) 进行了测试.
- 使用性和用户体验通过视频分析和"这个或那个"方法进行了评估.
主要成果:
- 大多数孩子完成了可用性任务,但所有人都需要帮助,突出了可用性挑战.
- 确定的问题包括食品分类,原型功能,产品召回和区分饮食场合.
- 产品偏好在原型中是相似的,但喜欢受到自主性,挑战,游戏,基于平板电脑的设计,外观,社交元素和时间的影响.
结论:
- 儿童可以补充父母的数据收集,以便更准确地评估饮食.
- 未来的工具需要培训,提示,反,直观的设计,儿童友好的视觉效果和自主性.
- 结果指导了儿童饮食评估和个性化营养支持方面的创新.
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