识别适应性移动健康干预措施的设计机会,以针对一般福祉为目标:与非正式护理合作伙伴的采访研究
Xinghui Yan1, Mark W Newman1, Sun Young Park1,2
1School of Information, University of Michigan, Ann Arbor, MI, United States.
JMIR formative research
|October 24, 2023
概括
非正规护理伙伴对移动健康 (mHealth) 信息的反应不同,根据感知的工作量,自我效能和意愿而采取的行动有所不同. 未来的干预措施应适应这些用户特定的行为,以优化支持.
科学领域:
- 数字健康数字健康
- 行为科学 行为科学
- 人与计算机的交互
背景情况:
- 移动健康 (mHealth) 干预为需要低负担解决方案的个人提供个性化支持.
- 该CareQOL mHealth应用程序已经显示出可行性和可接受性非正式的护理合作伙伴.
- 了解用户对mHealth信息的反应对于优化干预交付至关重要.
研究的目的:
- 调查影响护理合作伙伴决策和响应mHealth行为信息的行动的因素.
- 为更多量身定制和个性化的行为干预措施的发展提供信息.
主要方法:
- 与23名参与者进行半结构面试,这些参与者来自CareQOL应用程序随机对照试验的治疗组.
- 参与者获得了代表性的行为信息,以探讨它们对思想和行为的影响.
- 采访数据收集包括消息传递时间,自我报告的每日感知和用户消息评分.
主要成果:
- 护理合作伙伴对mHealth信息的反应不同,立即执行或调整行为或延迟 (长达一个月).
- 确定了影响这些变化的四个关键因素:感知工作量,规范行为能力,即时意愿/能力和整体参与能力.
- 用户的行动包括立即或延迟执行/适应建议的行为.
结论:
- 护理合作伙伴与mHealth行为信息的参与在即时性和适应性方面有所不同.
- 关于行为变化的认知和决策受到多个用户特定因素的影响.
- 未来的移动健康系统应该包含支持延迟或适应行为的功能,并根据已识别的影响因素量身定制支持.
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