Conversational AI and Vaccine Communication: a Systematic Review of the Evidence (Preprint)

Author:

Passanante AlyORCID,Pertwee EdORCID,Lin LeesaORCID,Lee Kristi YoonsupORCID,Wu Joseph T.ORCID,Larson Heidi J.

Abstract

BACKGROUND

During the early 2020s use of conversational AI (chatbots) in healthcare expanded significantly, especially in the context of increased burdens on health systems and restrictions on in-person consultations with healthcare providers during the COVID-19 pandemic. One emerging use case for conversational AI is related to communicating information about vaccines and vaccination.

OBJECTIVE

The objective of this systematic review was to examine documented uses and evidence on the effectiveness of conversational AI for vaccine communication.

METHODS

This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. PubMed, Web of Science, PsycINFO, Medline, Scopus, CINAHL Complete, Cochrane Library, EMBASE, Epistemonikos, Global Health, Global Index Medicus, Academic Search Complete and the University of London library database were searched for articles on the use of conversational AI for vaccine communication. The inclusion criteria were studies that included (1) documented instances of conversational AI being used for the purpose of vaccine communication, and (2) evaluation data on the impact and effectiveness of the intervention.

RESULTS

After duplicates were removed, the review identified 496 unique records which were then screened by title and abstract, of which 38 were identified for full text review. Eight fit the inclusion criteria and were assessed and summarized in the findings of this review. Overall, vaccine chatbots deployed to-date have been relatively simple in their design and have mainly been used to provide factual information to users about vaccines. Additionally, chatbots have been used for vaccination scheduling, appointment reminders, debunking misinformation and, in some cases, for vaccine counseling and persuasion. Available evidence suggests that chatbots can have a positive effect on vaccine attitudes; however, studies were typically exploratory in nature, and some lacked a control group and/or had very small sample sizes.

CONCLUSIONS

The review found evidence of potential benefits from conversational AI for vaccine communication. Factors that may contribute to the effectiveness of vaccine chatbots include their ability to provide credible and personalized information in real time, the familiarity and accessibility of the chatbot platform, and the extent to which interactions with the chatbot feel “natural” to users. However, evaluations have focused on the short-term, direct effects of chatbots on their users. The potential longer-term impacts of conversational AI on issues such as information literacy and public trust in healthcare have yet to be analyzed. In addition, existing studies do not adequately address how vaccination ethics apply in the field of conversational AI. Agreed ethical principles for this field are needed, especially since AI systems are now going beyond providing information and are engaging in vaccine counseling and persuasion. In a context where further digitalization of vaccine communication can be anticipated, additional high-quality research will be required across all these areas.

Publisher

JMIR Publications Inc.

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