Evidence map›Paper›PMID 35737898›Full record

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.

Rose Weeks, Lyra Cooper, Pooja Sangha, João Sedoc, Sydney White, Assaf Toledo, Shai Gretz, Dan Lahav, Nina Martin, Alexandra Michel and 3 more

2 registry-linked trialsOpen access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT06227689 naunknown statusnot on this mapstarted 2024, after this paper: background citation

Evaluation of Vaccine Chatbot on HPV Vaccine Awareness and Vaccination for Middle School Girls in China: a Randomized Controlled Trial and Implementation Science Study

TypeinterventionalSponsorFudan UniversityRan2024 to 2024Enrolled1,800ConditionsHPV VaccineArmsVaccine chatbot that offering HPV vaccine-related information
NCT07200570 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Evaluation of a Vaccine Chatbot on HPV Vaccine Confidence and Hesitancy: a Randomized Controlled Trial and Implementation Science Study

TypeinterventionalSponsorFudan UniversityRan2026 to 2026Enrolled1,800ConditionsHPV VaccineArmsLLM-Powered HPV Vaccine Chatbot
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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  10. 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 · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 2 countries.

Rose WeeksInternational Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-0171-5043
Lyra CooperInternational Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-1496-9854
Pooja SanghaInternational Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-6647-8299
João SedocStern School of Business, New York University, New York, NY, United States.ORCID 0000-0001-6369-3711
Sydney WhiteInternational Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-1798-3088
Assaf ToledoIBM Research AI, Haifa, Israel.ORCID 0000-0002-5309-267X
Shai GretzIBM Research AI, Haifa, Israel.ORCID 0000-0003-4562-7029
Dan LahavIBM Research AI, Haifa, Israel.ORCID 0000-0001-6602-8530
Nina MartinDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-3361-7037
Alexandra MichelInternational Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-7927-5968
Jae Hyoung LeeInternational Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-6303-086X
Noam SlonimIBM Research AI, Haifa, Israel.ORCID 0000-0001-5171-8264
Naor Bar-ZeevInternational Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-0570-4624
Johns Hopkins University · USIBM Research - Haifa · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19COVID-19 VaccinesAdolescentCommunicationHumansPublic HealthQualitative ResearchUnited StatesYoung AdultCOVID-19 VaccinesAIartificial intelligencechatbotsconversational agentCOVID-19digital healthhealth communicationinfodemicinfodemiologymisinformationnatural language processingonline health informationpublic healthsocial mediauser needvaccinationvaccine communicationvaccine hesitancy

Identifiers

PMID35737898
PMCPMC9301547
OpenAlexW4282941776

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.