Evidence map›Paper›PMID 36197708›Full record

ArticleJMIR human factors2022

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

Lee Wilson, Mariana Marasoiu

2 registry-linked trialsAbstract readScoping Review
In one paragraph

Article in JMIR human factors, 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 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed
–field-weighted citation impact
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

57 citing papers in PubMed.

  1. Article
  2. Communicating With Children With Cancer: Development of a Chatbot-Based Educational Support Tool.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026
    Article
  3. Observational
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. AI in hematology: A new frontier for nursing practice and patient care.Journal of family medicine and primary care · 2026
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review
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

2 authors.

Lee WilsonCentre for Policy Futures, University of Queensland, St Lucia, Queensland, Australia.ORCID https://orcid.org/0000-0002-9870-0907
Mariana MarasoiuDepartment of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-5917-3702

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChatbots 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.

objectiveThis 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.

methodsFollowing 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.

resultsOf 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.

conclusionsMore 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.

Indexed as

chatbot applicationchatbot developmentchatbotsconversational agentsCOVID-19digital healthevidencehealth care systemhealth technologymental healthpandemicpublic healthscoping review

Identifiers

PMID36197708
PMCPMC9536768

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.