JMIR Publications

ABSTRACT

Background:

Chatbots are computer programmes that present a conversational-like interface through which people can access information and services. The COVID-19 pandemic has driven a significant increase in the use of chatbots to support and complement traditional health care systems. However, despite the uptake in their use, evidence to support the development and deployment of chatbots in public health remains limited. Recent reviews have focused on the use of chatbots during COVID 19 and the use of conversational agents in healthcare more generally. The current paper complements this research and addresses a gap in the literature by assessing the breadth and scope of research evidence for use of chatbots across the domain of public health.

Objective:

This scoping review has three main objectives: i) to identify the application domains in public health in which there is most evidence for the development and use of chatbots; ii) to identify the types of chatbots that are being deployed in these domains; iii) to ascertain the methods and methodologies by which chatbots are being evaluated in public health applications. The paper explores the implications for future research on the development and deployment of chatbots in public health in light of analysis of the evidence for their use.

Methods:

Following Prisma ScR guidelines for scoping reviews, relevant studies were identified through searches conducted in the Medline, PubMed, Scopus, Cochrane Central Register of Controlled Trials, IEEE Xplore, ACM Digital Library, and Open Grey databases from mid-June through to August 2021. Studies were included if they employed or evaluated chatbots for the purpose of prevention or intervention, and for which the evidence showed a demonstrable health impact.

Results:

Of the 1506 studies identified, 32 were included in the review. Results show a significant increase in the interest of chatbots in the past few years, shortly before the pandemic. More the half of the research evaluated chatbots applied to mental health or COVID-19. The studies suggest promise in the application of chatbots, especially to easily automated and repetitive tasks, but overall, the evidence for the efficacy of chatbots for prevention and intervention across all domains is at present limited.

Conclusions:

More research is needed to fully understand the effectiveness of using chatbots in public health. Concerns with the clinical, legal, and ethical aspects of the use of chatbots for healthcare are well founded given the speed with which they have been adopted in practice. Future research on their use should address these concerns through the development of expertise and best practices specific to public health, including a greater focus on user experience.