ArticleJournal of medical Internet research2022
Chatbot-Delivered COVID-19 Vaccine Communication Message Preferences of Young Adults and Public Health Workers in Urban American Communities: Qualitative Study.
Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Evaluation of Vaccine Chatbot on HPV Vaccine Awareness and Vaccination for Middle School Girls in China: a Randomized Controlled Trial and Implementation Science Study
Evaluation of a Vaccine Chatbot on HPV Vaccine Confidence and Hesitancy: a Randomized Controlled Trial and Implementation Science Study
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review.Journal of medical Internet research · 2024Pooled it
- A vaccine chatbot intervention for parents to improve HPV vaccination uptake among middle school girls: a cluster randomized trial.Nature medicine · 2025Trial
- Chatbot-Delivered Online Intervention to Promote Seasonal Influenza Vaccination During the COVID-19 Pandemic: A Randomized Clinical Trial.JAMA network open · 2023Trial
- Engagement with a Chatbot-based Intervention for the delivery of mailed at-home COVID-19 Testing: a Descriptive Log Analysis Study from the SCALE-UP II Trial.medRxiv : the preprint server for health sciences · 2026Article
- Unlocking AI Chatbot Potential in Healthcare: Trust-Enhanced DeLone & McLean IS Success Model.Healthcare (Basel, Switzerland) · 2026Article
- Use of Artificial Intelligence in Public Health Education for Pandemic Preparedness and Response.Annals of global health · 2026Review
- The development and use of chatbots in enhancing health care access for underserved and vulnerable populations: a scoping review.BMC public health · 2025Article
- Effectiveness of conversational script optimization by intelligent consultation robots on daily work efficiency in vaccination clinics.Frontiers in public health · 2025Article
- Developing a Chatbot to Support Individuals With Neurodevelopmental Disorders: Tutorial.Journal of medical Internet research · 2024Article
- The performance of artificial intelligence chatbot large language models to address skeletal biology and bone health queries.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2024Article
- Using ChatGPT for Clinical Practice and Medical Education: Cross-Sectional Survey of Medical Students' and Physicians' Perceptions.JMIR medical education · 2023Article
- Patient portal interventions: a scoping review of functionality, automation used, and therapeutic elements of patient portal interventions.JAMIA open · 2023Article
- Article
- Usability and Credibility of a COVID-19 Vaccine Chatbot for Young Adults and Health Workers in the United States: Formative Mixed Methods Study.JMIR human factors · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAutomated conversational agents, or chatbots, have a role in reinforcing evidence-based guidance delivered through other media and offer an accessible, individually tailored channel for public engagement. In early-to-mid 2021, young adults and minority populations disproportionately affected by COVID-19 in the United States were more likely to be hesitant toward COVID-19 vaccines, citing concerns regarding vaccine safety and effectiveness. Successful chatbot communication requires purposive understanding of user needs.
objectiveWe aimed to review the acceptability of messages to be delivered by a chatbot named VIRA from Johns Hopkins University. The study investigated which message styles were preferred by young, urban-dwelling Americans as well as public health workers, since we anticipated that the chatbot would be used by the latter as a job aid.
methodsWe conducted 4 web-based focus groups with 20 racially and ethnically diverse young adults aged 18-28 years and public health workers aged 25-61 years living in or near eastern-US cities. We tested 6 message styles, asking participants to select a preferred response style for a chatbot answering common questions about COVID-19 vaccines. We transcribed, coded, and categorized emerging themes within the discussions of message content, style, and framing.
resultsParticipants preferred messages that began with an empathetic reflection of a user concern and concluded with a straightforward, fact-supported response. Most participants disapproved of moralistic or reasoning-based appeals to get vaccinated, although public health workers felt that such strong statements appealing to communal responsibility were warranted. Responses tested with humor and testimonials did not appeal to the participants.
conclusionsTo foster credibility, chatbots targeting young people with vaccine-related messaging should aim to build rapport with users by deploying empathic, reflective statements, followed by direct and comprehensive responses to user queries. Further studies are needed to inform the appropriate use of user-customized testimonials and humor in the context of chatbot communication.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.