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建模与依从性应用程序中的数字健康助手的对话:关于与熟悉的医疗接触的相似性和差异的一些考虑。

Modeling the Conversation with Digital Health Assistants in Adherence Apps: Some Considerations on the Similarities and Differences with Familiar Medical Encounters.

机构信息

Department of General Psychology, University of Padua, 35131 Padua, Italy.

Human Inspired Technologies Research Centre, University of Padua, 35131 Padua, Italy.

出版信息

Int J Environ Res Public Health. 2023 Jun 19;20(12):6182. doi: 10.3390/ijerph20126182.

Abstract

Digital health assistants (DHAs) are conversational agents incorporated into health systems' interfaces, exploiting an intuitive interaction format appreciated by the users. At the same time, however, their conversational format can evoke interactional practices typical of health encounters with human doctors that might misguide the users. Awareness of the similarities and differences between novel mediated encounters and more familiar ones helps designers avoid unintended expectations and leverage suitable ones. Focusing on adherence apps, we analytically discuss the structure of DHA-patient encounters against the literature on physician-patient encounters and the specific affordances of DHAs. We synthesize our discussion into a design checklist and add some considerations about DHA with unconstrained natural language interfaces.

摘要

数字健康助手 (DHAs) 是嵌入到健康系统界面中的会话代理,利用用户所欣赏的直观交互格式。然而,与此同时,它们的会话格式可能会唤起与人类医生进行健康互动的典型交互方式,从而误导用户。了解新型中介互动与更熟悉的互动之间的相似点和不同点,可以帮助设计师避免不必要的期望并利用合适的期望。本文聚焦于依从性应用程序,我们根据医患互动文献以及 DHA 的特定功能,对 DHA-患者互动的结构进行了分析性讨论。我们将讨论综合为一个设计检查表,并对具有非受限自然语言界面的 DHA 进行了一些考虑。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af22/10298441/7a2b52cbfcab/ijerph-20-06182-g001.jpg

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