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评估人工智能驱动的会话代理作为非传染性疾病远程管理中类人虚拟健康护理员的潜力和陷阱:范围综述。

Evaluating the Potential and Pitfalls of AI-Powered Conversational Agents as Humanlike Virtual Health Carers in the Remote Management of Noncommunicable Diseases: Scoping Review.

机构信息

Jeffrey Cheah School of Medicine & Health Sciences, Monash University Malaysia, Bandar Sunway, Malaysia.

Faculty of Information Technology, Data Future Institutes, Monash University, Clayton, Australia.

出版信息

J Med Internet Res. 2024 Jul 16;26:e56114. doi: 10.2196/56114.

Abstract

BACKGROUND

The rising prevalence of noncommunicable diseases (NCDs) worldwide and the high recent mortality rates (74.4%) associated with them, especially in low- and middle-income countries, is causing a substantial global burden of disease, necessitating innovative and sustainable long-term care solutions.

OBJECTIVE

This scoping review aims to investigate the impact of artificial intelligence (AI)-based conversational agents (CAs)-including chatbots, voicebots, and anthropomorphic digital avatars-as human-like health caregivers in the remote management of NCDs as well as identify critical areas for future research and provide insights into how these technologies might be used effectively in health care to personalize NCD management strategies.

METHODS

A broad literature search was conducted in July 2023 in 6 electronic databases-Ovid MEDLINE, Embase, PsycINFO, PubMed, CINAHL, and Web of Science-using the search terms "conversational agents," "artificial intelligence," and "noncommunicable diseases," including their associated synonyms. We also manually searched gray literature using sources such as ProQuest Central, ResearchGate, ACM Digital Library, and Google Scholar. We included empirical studies published in English from January 2010 to July 2023 focusing solely on health care-oriented applications of CAs used for remote management of NCDs. The narrative synthesis approach was used to collate and summarize the relevant information extracted from the included studies.

RESULTS

The literature search yielded a total of 43 studies that matched the inclusion criteria. Our review unveiled four significant findings: (1) higher user acceptance and compliance with anthropomorphic and avatar-based CAs for remote care; (2) an existing gap in the development of personalized, empathetic, and contextually aware CAs for effective emotional and social interaction with users, along with limited consideration of ethical concerns such as data privacy and patient safety; (3) inadequate evidence of the efficacy of CAs in NCD self-management despite a moderate to high level of optimism among health care professionals regarding CAs' potential in remote health care; and (4) CAs primarily being used for supporting nonpharmacological interventions such as behavioral or lifestyle modifications and patient education for the self-management of NCDs.

CONCLUSIONS

This review makes a unique contribution to the field by not only providing a quantifiable impact analysis but also identifying the areas requiring imminent scholarly attention for the ethical, empathetic, and efficacious implementation of AI in NCD care. This serves as an academic cornerstone for future research in AI-assisted health care for NCD management.

TRIAL REGISTRATION

Open Science Framework; https://doi.org/10.17605/OSF.IO/GU5PX.

摘要

背景

全球范围内非传染性疾病(NCDs)的患病率不断上升,以及与之相关的高死亡率(74.4%),尤其是在低收入和中等收入国家,这导致了巨大的全球疾病负担,需要创新和可持续的长期护理解决方案。

目的

本范围综述旨在调查基于人工智能(AI)的会话代理(CA)-包括聊天机器人、语音机器人和拟人化数字虚拟形象-作为类似人类的健康护理者,在 NCD 的远程管理中的作用,并确定未来研究的关键领域,并提供关于这些技术如何在医疗保健中有效使用以个性化 NCD 管理策略的见解。

方法

2023 年 7 月,我们在 6 个电子数据库(Ovid MEDLINE、Embase、PsycINFO、PubMed、CINAHL 和 Web of Science)中使用“会话代理”、“人工智能”和“非传染性疾病”等搜索词进行了广泛的文献检索,并包括其相关同义词。我们还使用 ProQuest Central、ResearchGate、ACM 数字图书馆和 Google Scholar 等来源手动搜索灰色文献。我们纳入了 2010 年 1 月至 2023 年 7 月期间仅专注于 CA 在 NCD 远程管理中的医疗保健应用的以英语发表的实证研究。我们采用叙述性综合方法来整理和总结从纳入研究中提取的相关信息。

结果

文献检索共得到 43 项符合纳入标准的研究。我们的综述揭示了四项重要发现:(1)用户对远程护理中拟人化和基于虚拟形象的 CA 的接受度和依从性更高;(2)在为有效进行情感和社交互动而开发个性化、有同理心和情境感知的 CA 方面存在差距,同时对数据隐私和患者安全等伦理问题的考虑有限;(3)尽管医疗保健专业人员对 CA 在远程医疗中的潜力持中度至高度乐观态度,但 CA 在 NCD 自我管理中的疗效证据不足;(4)CA 主要用于支持非药物干预,如行为或生活方式改变和患者教育,以自我管理 NCD。

结论

本综述通过不仅提供量化影响分析,还确定了需要立即引起学者关注的领域,为 NCD 护理中 AI 的伦理、有同理心和有效的实施做出了独特贡献。这为 AI 辅助 NCD 管理的未来研究提供了学术基础。

试验注册

Open Science Framework;https://doi.org/10.17605/OSF.IO/GU5PX。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b565/11289576/cb26bae8b30f/jmir_v26i1e56114_fig1.jpg

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