The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review.
The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review.
复制标题
DOI：
10.2196/20346
复制
发表时间：
2020-10-22
影响因子：
7.4
通讯作者：
Meinert E
中科院分区：
文献类型：
--
作者：
Milne-Ives M;de Cock C;Lim E;Shehadeh MH;de Pennington N;Mole G;Normando E;Meinert E
对医疗保健服务的高需求和人工智能能力的不断增长导致了旨在支持各种健康相关活动的会话代理的发展，包括行为改变，治疗支持，健康监测，培训，分流和筛查支持。这些任务的自动化可以使临床医生专注于更复杂的工作，并增加公众获得医疗保健服务的机会。需要对这些药物在医疗保健中的可接受性、可用性和有效性进行全面评估，以整理证据，以便未来的发展能够针对需要改进的领域和可持续采用的潜力。这篇系统性综述旨在评估会话代理在医疗保健中的有效性和可用性，并确定用户喜欢和不喜欢的元素，以告知这些代理的未来研究和开发。对PubMed、Medline（奥维德）、EMBASE（Excerpta Medica dataBASE）、CINAHL（护理和相关健康文献累积索引）、Web of Science和计算机协会数字图书馆进行了系统性检索，以查找自2008年以来发表的评价医疗保健中使用的无约束自然语言处理会话代理的文章。使用EndNote（版本X9，Clarivate Analytics）参考文献管理软件进行初始筛选，由1名审查员进行全文筛选。提取数据，由一位评审员评估偏倚风险，并由另一位评审员进行验证。共选择了31项研究，包括各种对话代理，包括14个聊天机器人（其中2个是语音聊天机器人），6个具体的对话代理（其中3个是交互式语音应答呼叫，虚拟患者和语音识别筛选系统），1个上下文问答代理和1个语音识别分流系统。总体而言，报告的证据大多是积极的或好坏参半。可用性和满意度表现良好（27/30和26/31），四分之三的研究（23/30）发现了积极或混合的有效性。然而，在具体的质量反馈中，强调了代理人的一些局限性。这些研究普遍报告了积极或混合的证据的有效性，可用性和可靠性的会话代理人的调查，但定性用户的看法更为复杂。许多研究的质量有限，需要改进研究设计和报告，以更准确地评估药物在医疗保健中的有用性，并确定需要改进的关键领域。进一步的研究还应该分析代理的成本效益，隐私和安全性。RR2-10.2196/16934
The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversational agents designed to support a variety of health-related activities, including behavior change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase the accessibility to health care services for the public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in health care is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption. This systematic review aims to assess the effectiveness and usability of conversational agents in health care and identify the elements that users like and dislike to inform future research and development of these agents. PubMed, Medline (Ovid), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and the Association for Computing Machinery Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in health care. EndNote (version X9, Clarivate Analytics) reference management software was used for initial screening, and full-text screening was conducted by 1 reviewer. Data were extracted, and the risk of bias was assessed by one reviewer and validated by another. A total of 31 studies were selected and included a variety of conversational agents, including 14 chatbots (2 of which were voice chatbots), 6 embodied conversational agents (3 of which were interactive voice response calls, virtual patients, and speech recognition screening systems), 1 contextual question-answering agent, and 1 voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31), and positive or mixed effectiveness was found in three-quarters of the studies (23/30). However, there were several limitations of the agents highlighted in specific qualitative feedback. The studies generally reported positive or mixed evidence for the effectiveness, usability, and satisfactoriness of the conversational agents investigated, but qualitative user perceptions were more mixed. The quality of many of the studies was limited, and improved study design and reporting are necessary to more accurately evaluate the usefulness of the agents in health care and identify key areas for improvement. Further research should also analyze the cost-effectiveness, privacy, and security of the agents. RR2-10.2196/16934
登录
查看更多内容
影响因子：
7.6
作者：
Crutzen, Rik;Peters, Gjalt-Jorn Y.;Grolleman, Jorne J.
通讯作者：
Grolleman, Jorne J.
影响因子：
5
作者：
Inkster B;Sarda S;Subramanian V
通讯作者：
Subramanian V
影响因子：
7
作者：
Dimeff, Linda A.;Jobes, David A.;Koerner, Kelly
通讯作者：
Koerner, Kelly
影响因子：
2.5
作者：
Campillos-Llanos，Leonardo;Thomas，Catherine;Rosset，Sophie
通讯作者：
Rosset，Sophie
影响因子：
1.2
作者：
Borja-Hart, Nancy L.;Spivey, Christina A.;George, Christa M.
通讯作者：
George, Christa M.