Yuan Fengpei, Zhou Wenjun, Dodge Hiroko H, Zhao Xiaopeng
Department of Mechanical, Aerospace and Biomedical Engineering, The University of Tennessee Knoxville, 1512 Middle Drive, Knoxville, TN, 37996, USA.
Department of Business Analytics and Statistics, The University of Tennessee Knoxville, 916 Volunteer Blvd., Knoxville, TN, 37996, USA.
Smart Health (Amst). 2023 Jun;28. doi: 10.1016/j.smhl.2023.100384. Epub 2023 Mar 21.
Social isolation has become a growing public health concern in older adults and older adults with mild cognitive impairment. Coping strategies must be developed to increase social contact for socially isolated older adults. In this paper, we explored the conversational strategy between trained conversation moderators and socially isolated adults during a conversational engagement clinical trial (Clinicaltrials.gov: NCT02871921). We carried out structural learning and causality analysis to investigate the conversation strategies used by the trained moderators to engage socially isolated adults in the conversation and the causal effects of the strategy on engagement. Causal relations and effects were inferred between participants' emotions, the dialogue strategies used by moderators, and participants' following emotions. The results found in this paper may be used to support the development of cost-efficient, trustworthy AI- and/or robot-based platform to promote conversational engagement for older adults to address the challenges in social interaction.
社交隔离已成为老年人以及患有轻度认知障碍的老年人日益关注的公共卫生问题。必须制定应对策略,以增加社交隔离老年人的社交接触。在本文中,我们在一项对话参与临床试验(Clinicaltrials.gov:NCT02871921)中,探讨了经过培训的对话主持人与社交隔离成年人之间的对话策略。我们进行了结构学习和因果分析,以调查经过培训的主持人用于使社交隔离成年人参与对话的对话策略,以及该策略对参与度的因果效应。推断出参与者的情绪、主持人使用的对话策略和参与者随后的情绪之间的因果关系和影响。本文的研究结果可用于支持开发具有成本效益、值得信赖的基于人工智能和/或机器人的平台,以促进老年人的对话参与,应对社交互动中的挑战。