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基于移动应用的关系型代理作为 COVID-19 患者的健康专业人员:设计、方法和意义。

A Mobile Application-Based Relational Agent as a Health Professional for COVID-19 Patients: Design, Approach, and Implications.

机构信息

School of Computing and Informatics, University of Louisiana at Lafayette, 301 East Lewis Street, Lafayette, LA 70503, USA.

出版信息

Int J Environ Res Public Health. 2022 Oct 24;19(21):13794. doi: 10.3390/ijerph192113794.

DOI:10.3390/ijerph192113794
PMID:36360674
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9656668/
Abstract

Relational Agents' (RAs) ability to maintain socio-emotional relationships with users can be an asset to COVID-19 patients. The goal of this research was to identify principles for designing an RA that can act as a health professional for a COVID-19 patient. We first identified tasks that such an RA can provide by interviewing 33 individuals, who had recovered from COVID-19. The transcribed interviews were analyzed using qualitative thematic analysis. Based on the findings, four sets of hypothetical conversations were handcrafted to illustrate how the proposed RA will execute the identified tasks. These conversations were then evaluated by 43 healthcare professionals in a qualitative study. Thematic analysis was again used to identify characteristics that would be suitable for the proposed RA. The results suggest that the RA must: model clinical protocols; incorporate evidence-based interventions; inform, educate, and remind patients; build trusting relationships, and support their socio-emotional needs. The findings have implications for designing RAs for other healthcare contexts beyond the pandemic.

摘要

关系型代理(RAs)与用户保持社会情感关系的能力可能是 COVID-19 患者的一项资产。本研究的目的是确定设计能够充当 COVID-19 患者健康专业人员的 RA 的原则。我们首先通过采访 33 名从 COVID-19 中康复的个体来确定此类 RA 可以提供的任务。对转录的访谈进行了定性主题分析。根据研究结果,手工制作了四组假设对话,以说明拟议的 RA 将如何执行确定的任务。然后,43 名医疗保健专业人员在一项定性研究中对这些对话进行了评估。再次使用主题分析来确定适合拟议 RA 的特征。结果表明,RA 必须:模拟临床方案;纳入基于证据的干预措施;告知、教育和提醒患者;建立信任关系,并满足他们的社会情感需求。研究结果对设计大流行以外其他医疗保健环境的 RAs 具有启示意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72d9/9656668/c3b93ebdfe07/ijerph-19-13794-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72d9/9656668/c3b93ebdfe07/ijerph-19-13794-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72d9/9656668/c3b93ebdfe07/ijerph-19-13794-g001.jpg

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