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以患者为中心的护理中注重健康的对话代理:应用程序综述

Health-focused conversational agents in person-centered care: a review of apps.

作者信息

Parmar Pritika, Ryu Jina, Pandya Shivani, Sedoc João, Agarwal Smisha

机构信息

The Johns Hopkins University Krieger School of Arts and Sciences, Baltimore, MD, USA.

Department of International Health, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.

出版信息

NPJ Digit Med. 2022 Feb 17;5(1):21. doi: 10.1038/s41746-022-00560-6.

Abstract

Health-focused apps with chatbots ("healthbots") have a critical role in addressing gaps in quality healthcare. There is limited evidence on how such healthbots are developed and applied in practice. Our review of healthbots aims to classify types of healthbots, contexts of use, and their natural language processing capabilities. Eligible apps were those that were health-related, had an embedded text-based conversational agent, available in English, and were available for free download through the Google Play or Apple iOS store. Apps were identified using 42Matters software, a mobile app search engine. Apps were assessed using an evaluation framework addressing chatbot characteristics and natural language processing features. The review suggests uptake across 33 low- and high-income countries. Most healthbots are patient-facing, available on a mobile interface and provide a range of functions including health education and counselling support, assessment of symptoms, and assistance with tasks such as scheduling. Most of the 78 apps reviewed focus on primary care and mental health, only 6 (7.59%) had a theoretical underpinning, and 10 (12.35%) complied with health information privacy regulations. Our assessment indicated that only a few apps use machine learning and natural language processing approaches, despite such marketing claims. Most apps allowed for a finite-state input, where the dialogue is led by the system and follows a predetermined algorithm. Healthbots are potentially transformative in centering care around the user; however, they are in a nascent state of development and require further research on development, automation and adoption for a population-level health impact.

摘要

带有聊天机器人的健康类应用程序(“健康机器人”)在弥补优质医疗保健差距方面发挥着关键作用。关于此类健康机器人如何在实践中开发和应用的证据有限。我们对健康机器人的综述旨在对健康机器人的类型、使用场景及其自然语言处理能力进行分类。符合条件的应用程序是那些与健康相关、具有嵌入式基于文本的对话代理、以英文提供且可通过谷歌应用商店或苹果iOS商店免费下载的应用程序。使用移动应用搜索引擎42Matters软件识别应用程序。使用一个涉及聊天机器人特征和自然语言处理功能的评估框架对应用程序进行评估。该综述表明,此类应用程序在33个低收入和高收入国家得到了应用。大多数健康机器人面向患者,可在移动界面上使用,并提供一系列功能,包括健康教育和咨询支持、症状评估以及诸如安排日程等任务的协助。在审查的78个应用程序中,大多数侧重于初级保健和心理健康,只有6个(7.59%)有理论基础,10个(12.35%)符合健康信息隐私法规。我们的评估表明,尽管有此类营销宣传,但只有少数应用程序使用机器学习和自然语言处理方法。大多数应用程序允许有限状态输入,即对话由系统主导并遵循预定算法。健康机器人在以用户为中心提供护理方面可能具有变革性;然而,它们尚处于发展初期,需要在开发、自动化和采用方面进行进一步研究,以对人群健康产生影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d99/8854396/9811db5b3183/41746_2022_560_Fig1_HTML.jpg

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