Center for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.
Future Health Technologies Programme, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore-ETH Centre, Singapore, Singapore.
J Med Internet Res. 2021 Mar 29;23(3):e25933. doi: 10.2196/25933.
Chronic and mental health conditions are increasingly prevalent worldwide. As devices in our everyday lives offer more and more voice-based self-service, voice-based conversational agents (VCAs) have the potential to support the prevention and management of these conditions in a scalable manner. However, evidence on VCAs dedicated to the prevention and management of chronic and mental health conditions is unclear.
This study provides a better understanding of the current methods used in the evaluation of health interventions for the prevention and management of chronic and mental health conditions delivered through VCAs.
We conducted a systematic literature review using PubMed MEDLINE, Embase, PsycINFO, Scopus, and Web of Science databases. We included primary research involving the prevention or management of chronic or mental health conditions through a VCA and reporting an empirical evaluation of the system either in terms of system accuracy, technology acceptance, or both. A total of 2 independent reviewers conducted the screening and data extraction, and agreement between them was measured using Cohen kappa. A narrative approach was used to synthesize the selected records.
Of 7170 prescreened papers, 12 met the inclusion criteria. All studies were nonexperimental. The VCAs provided behavioral support (n=5), health monitoring services (n=3), or both (n=4). The interventions were delivered via smartphones (n=5), tablets (n=2), or smart speakers (n=3). In 2 cases, no device was specified. A total of 3 VCAs targeted cancer, whereas 2 VCAs targeted diabetes and heart failure. The other VCAs targeted hearing impairment, asthma, Parkinson disease, dementia, autism, intellectual disability, and depression. The majority of the studies (n=7) assessed technology acceptance, but only few studies (n=3) used validated instruments. Half of the studies (n=6) reported either performance measures on speech recognition or on the ability of VCAs to respond to health-related queries. Only a minority of the studies (n=2) reported behavioral measures or a measure of attitudes toward intervention-targeted health behavior. Moreover, only a minority of studies (n=4) reported controlling for participants' previous experience with technology. Finally, risk bias varied markedly.
The heterogeneity in the methods, the limited number of studies identified, and the high risk of bias show that research on VCAs for chronic and mental health conditions is still in its infancy. Although the results of system accuracy and technology acceptance are encouraging, there is still a need to establish more conclusive evidence on the efficacy of VCAs for the prevention and management of chronic and mental health conditions, both in absolute terms and in comparison with standard health care.
慢性疾病和精神健康问题在全球范围内日益普遍。随着我们日常生活中的设备提供越来越多的基于语音的自助服务，基于语音的对话代理（VCA）有可能以可扩展的方式支持这些疾病的预防和管理。然而，针对 VCA 在预防和管理慢性和精神健康问题方面的专门证据尚不清楚。
本研究旨在更好地了解当前用于评估通过 VCA 预防和管理慢性和精神健康问题的健康干预措施的方法。
我们使用 PubMed MEDLINE、Embase、PsycINFO、Scopus 和 Web of Science 数据库进行了系统文献综述。我们纳入了通过 VCA 预防或管理慢性或精神健康问题的初级研究，并报告了系统在系统准确性、技术接受度或两者方面的实证评估。2 位独立审查员进行了筛选和数据提取，并使用 Cohen kappa 测量了他们之间的一致性。采用叙述方法综合所选记录。
在 7170 篇预筛选论文中，有 12 篇符合纳入标准。所有研究均为非实验性研究。VCA 提供行为支持（n=5）、健康监测服务（n=3）或两者兼有（n=4）。干预措施通过智能手机（n=5）、平板电脑（n=2）或智能扬声器（n=3）进行传递。在 2 种情况下，均未指定设备。共有 3 个 VCA 针对癌症，2 个 VCA 针对糖尿病和心力衰竭。其他的 VCA 针对听力障碍、哮喘、帕金森病、痴呆、自闭症、智力残疾和抑郁症。大多数研究（n=7）评估了技术接受度，但只有少数研究（n=3）使用了经过验证的工具。一半的研究（n=6）报告了语音识别的性能指标，或 VCA 对健康相关查询的响应能力。只有少数研究（n=2）报告了行为措施或干预目标健康行为的态度衡量标准。此外，只有少数研究（n=4）报告了控制参与者之前的技术使用经验。最后，风险偏差差异很大。
方法的异质性、确定的研究数量有限以及高偏倚风险表明，针对慢性和精神健康问题的 VCA 研究仍处于起步阶段。尽管系统准确性和技术接受度的结果令人鼓舞，但仍需要在 VCA 预防和管理慢性和精神健康问题的疗效方面建立更确凿的证据，无论是在绝对意义上还是与标准医疗保健相比。
