谁需要什么 (功能) 什么时候? 个性化参与数据驱动的自我管理,以改善健康公平
Marissa Burgermaster1, Pooja M Desai2, Elizabeth M Heitkemper3
1Department of Nutritional Sciences, The University Of Texas At Austin, Department Of Population Health, Dell Medical School, Austin, TX, United States.
Journal of biomedical informatics
|June 10, 2023
概括
使用自决理论 (SDT) 量身定制的mHealth应用程序有望改善服务不足社区的健康自我管理. 然而,设计需要更好地与动机类型保持一致,并为外部监管提供更强大的情感支持.
科学领域:
- 数字健康数字健康
- 行为科学 行为科学
- 健康差异 在健康上的差异
背景情况:
- 少数群体和医疗服务不足的社区在管理2型糖尿病等慢性疾病方面面临着独特的挑战.
- 自决理论 (SDT) 为理解健康行为中的动机和调节提供了一个框架.
- 移动健康干预提供了一个可扩展的方法来支持健康自我管理.
研究的目的:
- 评估将mHealth应用程序设计定制为数据驱动的健康自我管理的可行性.
- 根据SDT,使干预设计与个人的动机和监管类型保持一致.
- 改善来自少数群体,医疗服务不足社区的个人之间的参与.
主要方法:
- 来自一个贫困的少数民族社区的53名2型糖尿病患者参与了这项研究.
- 参与者被随机分配到四个版本的mHealth应用程序 (Platano),每个版本都针对特定的SDT动机/监管类型量身定制.
- 定性访谈探讨了应用程序功能,用户动机和体验之间的相互作用.
主要成果:
- 观察到用户动机类型和定制应用程序功能的有效性之间存在显著的相互作用.
- 有更多内在动机的人对自我评估和个性化预测功能做出了更好的反应.
- 针对外部调节的特征显示出不太理想的结果,可能是由于缺乏足够的情感支持.
结论:
- 使用SDT定制移动健康干预措施是可行的,以促进数据驱动的自我管理.
- 需要进一步的研究来完善设计,以满足不同的动机水平,并增强情感支持.
- 解决健康素养和资源获取问题对于服务不足的人群至关重要.
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