The Development and Use of Chatbots in Public Health: Scoping Review

Lee Wilson, Mariana Marasoiu, Lee Wilson, Mariana Marasoiu

Abstract

Background: Chatbots are computer programs that present a conversation-like interface through which people can access information and services. The COVID-19 pandemic has driven a substantial 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 the COVID-19 pandemic and the use of conversational agents in health care more generally. This paper complements this research and addresses a gap in the literature by assessing the breadth and scope of research evidence for the use of chatbots across the domain of public health.

Objective: This scoping review had 3 main objectives: (1) to identify the application domains in public health in which there is the most evidence for the development and use of chatbots; (2) to identify the types of chatbots that are being deployed in these domains; and (3) to ascertain the methods and methodologies by which chatbots are being evaluated in public health applications. This paper explored the implications for future research on the development and deployment of chatbots in public health in light of the analysis of the evidence for their use.

Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) 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 to August 2021. Studies were included if they used 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. The results show a substantial increase in the interest of chatbots in the past few years, shortly before the pandemic. Half (16/32, 50%) 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 limited at present.

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 health care 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.

Keywords: COVID-19; chatbot application; chatbot development; chatbots; conversational agents; digital health; evidence; health care system; health technology; mental health; pandemic; public health; scoping review.

Conflict of interest statement

Conflicts of Interest: The original study that is the basis of this paper was commissioned by the World Health Organization. MM is a contractor of Katikati, a social technology start-up enabling 1-to-1 human-led conversations at scale over SMS text messaging, instant messaging, or web.

©Lee Wilson, Mariana Marasoiu. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 05.10.2022.

Figures

Figure 1
Figure 1
Review selection process.
Figure 2
Figure 2
Distribution of included publications across application domains. Mental health research and COVID-19 form the majority of the studies. Due to the small numbers of papers, percentages must be interpreted with caution and only indicate the presence of research in the area rather than an accurate distribution of research.
Figure 3
Figure 3
Distribution of included publications across application domains and publication year. Mental health research has a continued interest over time, with COVID-19–related research showing strong recent interest as expected.
Figure 4
Figure 4
Distribution of chatbot platforms in the included studies. PC: personal computer.
Figure 5
Figure 5
The ways in which users could message the chatbot were either by choosing from a set of predefined options or freely typing text as in a typical messaging app.
Figure 6
Figure 6
Presentation of the chatbot avatar.

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