基于流量理论的远程生命目标设定的人工智能支持的mHealth干预的可行性和用户体验:探索性参与者内部研究
1Department of Occupational Therapy, Faculty of Health Sciences, Wakayama Professional University of Rehabilitation, Wakayama, Japan.
JMIR formative research
|January 27, 2026
概括
使用生成性人工智能的移动健康干预对生活目标设定是可行的,并且得到了很好的接受,在动机和立即支持方面提供了优势. 职业治疗师的支持通过促进反思和心理安全来补充AI.
科学领域:
- 数字健康数字健康
- 人工智能的人工智能
- 行为科学 行为科学
背景情况:
- 设定生活目标显著影响幸福,但远程支持面临着可访问性挑战.
- 移动健康 (mHealth),远程医疗和生成AI为个性化的健康干预提供了可扩展的解决方案.
- 很少有研究将人工智能驱动的目标干预与现实环境中人类促进的方法进行比较.
研究的目的:
- 评估基于流量理论的远程生活目标设定人工智能支持的mHealth干预的可行性和用户体验.
- 将人工智能支持的目标设定与职业治疗师 (OT) 促进的支持进行比较.
- 探索人工智能指导与人类指导的干预对自我管理和动机的差异性特征.
主要方法:
- 在28名智能手机用户中进行了探索性,参与者内部,两种条件的比较 (AI与OT).
- 参与者完成了远程调整挑战-技能平衡 (R-ACS) 会议,以实现两个个人目标.
- 通过基于标签的问卷和自由文本反收集的数据;使用Wilcoxon签名等级测试和文本挖掘进行分析.
主要成果:
- 人工智能和OT干预都是可行的,提供量身定制的建议.
- 由人工智能支持的会议在建议的适当性 (P=.008) 和总体标题项目方面得分更高.
- 人工智能强调可操作性和动机;OTs强调反思和情绪安全. 两者都得到了很好的接受.
结论:
- 人工智能支持的生命目标设定mHealth干预措施是可行的,被接受的,并增强动机和行动.
- OT支持在反思和心理安全方面提供了互补的好处.
- 混合AI-OT模型可以优化可扩展的,个性化的目标设定支持.
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