一个社会辅助机器人的可接受性和可用性,与一个大型语言模型集成,用于在老年护理机构中加强人机交互:混合方法评估
Lauriane Blavette1,2,3, Sébastien Dacunha1,2,3, Xavier Alameda-Pineda4
1Institut national de la santé et de la recherche médicale - Optimisation thérapeutique en pharmacologie OTEN U1144, Université Paris Cité, Paris, France.
JMIR human factors
|August 1, 2025
概括
社会辅助机器人 (SARs) 在老年护理环境中显示出更好的接受性和可用性. 改进,特别是大型语言模型 (LLM),显著提高了老年人和护理人员的用户满意度和交互质量.
科学领域:
- 老年人护理技术的技术.
- 人与机器人的互动
- 辅助机器人的机器人技术
背景情况:
- 社会辅助机器人 (SAR) 为医院中的老年人 (OA) 提供了潜在的好处,包括社会参与和减少孤独感.
- 然而,接受性和可用性的挑战阻碍了它们在现实世界护理环境中的采用.
研究的目的:
- 评估SAR在老年人日托医院 (DCH) 的可接受性和可用性.
- 确定影响OA和非正式护理人员采用SAR的因素.
主要方法:
- 对ARI机器人进行了一年多的混合方法评估,97名参与者 (OA和非正式护理人员).
- 在基于语音的交互后,收集了标准化评估 (AES,SUS) 和定性反.
- 该研究涉及代部署和系统增强,包括LLM集成.
主要成果:
- 可接受性和可用性得分随着时间的推移显著增加 (P<.001).
- 在可接受性和可用性之间发现了强烈的正相关性 (r=0.664,P<.001).
- 整合一个大型语言模型 (LLM) 改善了交互的连贯性,自然性和上下文意识.
结论:
- 代系统增强,特别是LLM集成,可测量地提高了SAR的可用性和可接受性.
- 以用户为中心的设计对于成功地在老年护理中部署SAR至关重要.
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