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The Effectiveness of Conversational AI Service (chatbot) Utilization on Vaccine Confidence

NCT ID: NCT05424952

Last Updated: 2024-12-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

1000 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-02-11

Study Completion Date

2023-02-17

Brief Summary

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The primary objective of this study is to develop and evaluate a conversational AI service (chatbot) on social media platforms to obtain accurate and up-to-date vaccine information, and assess the impact of chatbot usage on users' vaccine confidence and acceptance in Hong Kong, Singapore, and Thailand.

Detailed Description

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The investigators will focus on vulnerable seniors and/or children from Hong Kong, Singapore and Thailand who have refused or delayed COVID-19 vaccination. Participants will be recruited by an online panel to meet the target quota by age and sex. Participants will then be randomly assigned to the intervention group and the control group. For both intervention and control groups, evaluation questionnaires will be given out to the study participants asking questions about their demographics, including age, sex, educational level, employment status and household income levels. Participants will then answer questions regarding COVID-19 vaccine confidence, including the effectiveness and safety of vaccines, and the motivations of the policymakers who decided on the needed vaccines. Participants will be asked about COVID-19 vaccine acceptance including the intention to receive COVID-19 vaccines, make plans to receive COVID-19 vaccines, and receive at least one dose of COVID-19 vaccines. The intervention group will then be asked to use the chatbot developed by the research team for up to two weeks. The chatbot is developed under the RE-AIM framework for formative, impact, and process evaluation of the intervention. The control group will have no exposure to the chatbot.

The chatbot will be supported with data from 1) social listening analytics for monitoring local real-time discourses in the digital space on COVID-19 vaccine hesitancy and misinformation, and 2) formative, baseline, and endpoint evaluation, which will generate evidence for development and improvement/refinement.

Conditions

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Vaccination Hesitancy

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

DOUBLE

Participants Investigators

Study Groups

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Control

Eligible adults with unvaccinated senior parents/grandparents or children.

Group Type NO_INTERVENTION

No interventions assigned to this group

Intervention

Eligible adults with unvaccinated senior parents/grandparents or children.

Group Type EXPERIMENTAL

Conversational AI Service (Chatbot)

Intervention Type OTHER

WhatsApp or Messenger Chatbot for COVID-19 vaccines

Interventions

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Conversational AI Service (Chatbot)

WhatsApp or Messenger Chatbot for COVID-19 vaccines

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Hong Kong adult residents (English or Chinese users) with (a) unvaccinated senior parents/grandparents aged 60 (including those who received first dose after the announcement of the COVID passport on 4th of January) or (b) unvaccinated children aged below 18.
* Thailand adult residents (Thai users) with (a) unvaccinated senior parents/grandparents aged 60 or above or (b) unvaccinated children aged below 18.
* Singapore adult residents (English or Chinese users) with unvaccinated children aged between 5 to 11 years old.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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National University of Singapore

OTHER

Sponsor Role collaborator

Health Intervention and Technology Assessment Program (HITAP)

UNKNOWN

Sponsor Role collaborator

The University of Hong Kong

OTHER

Sponsor Role lead

Responsible Party

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Joseph Tsz Kei Wu

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Joseph T Wu, PhD

Role: PRINCIPAL_INVESTIGATOR

The University of Hong Kong

Locations

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The University of Hong Kong

Hong Kong, , Hong Kong

Site Status

National University of Singapore

Singapore, , Singapore

Site Status

Health Intervention and Technology Assessment Program

Bangkok, , Thailand

Site Status

Countries

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Hong Kong Singapore Thailand

References

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Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999 Sep;89(9):1322-7. doi: 10.2105/ajph.89.9.1322.

Reference Type BACKGROUND
PMID: 10474547 (View on PubMed)

Gaglio B, Shoup JA, Glasgow RE. The RE-AIM framework: a systematic review of use over time. Am J Public Health. 2013 Jun;103(6):e38-46. doi: 10.2105/AJPH.2013.301299. Epub 2013 Apr 18.

Reference Type BACKGROUND
PMID: 23597377 (View on PubMed)

Kobayashi T, Nishina Y, Tomoi H, et al. Corowa-kun: Impact of a COVID-19 vaccine information chatbot on vaccine hesitancy, Japan 2021. medRxiv 2021: 2021.05.26.21257854.

Reference Type BACKGROUND

de Figueiredo A, Simas C, Karafillakis E, Paterson P, Larson HJ. Mapping global trends in vaccine confidence and investigating barriers to vaccine uptake: a large-scale retrospective temporal modelling study. Lancet. 2020 Sep 26;396(10255):898-908. doi: 10.1016/S0140-6736(20)31558-0. Epub 2020 Sep 10.

Reference Type BACKGROUND
PMID: 32919524 (View on PubMed)

Larson HJ, Smith DM, Paterson P, Cumming M, Eckersberger E, Freifeld CC, Ghinai I, Jarrett C, Paushter L, Brownstein JS, Madoff LC. Measuring vaccine confidence: analysis of data obtained by a media surveillance system used to analyse public concerns about vaccines. Lancet Infect Dis. 2013 Jul;13(7):606-613. doi: 10.1016/S1473-3099(13)70108-7. Epub 2013 May 13.

Reference Type BACKGROUND
PMID: 23676442 (View on PubMed)

Wang Q, Yang L, Jin H, Lin L. Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors. Prev Med. 2021 Sep;150:106694. doi: 10.1016/j.ypmed.2021.106694. Epub 2021 Jun 22.

Reference Type BACKGROUND
PMID: 34171345 (View on PubMed)

Zhang J, Featherstone JD, Calabrese C, Wojcieszak M. Effects of fact-checking social media vaccine misinformation on attitudes toward vaccines. Prev Med. 2021 Apr;145:106408. doi: 10.1016/j.ypmed.2020.106408. Epub 2021 Jan 1.

Reference Type BACKGROUND
PMID: 33388335 (View on PubMed)

Altay S, Hacquin AS, Chevallier C, Mercier H. Information delivered by a chatbot has a positive impact on COVID-19 vaccines attitudes and intentions. J Exp Psychol Appl. 2023 Mar;29(1):52-62. doi: 10.1037/xap0000400. Epub 2021 Oct 28.

Reference Type BACKGROUND
PMID: 34726454 (View on PubMed)

Thomala LL. Penetration rate of leading social networks in Hong Kong as of 3rd quarter 2020 (Link: https://www.statista.com/statistics/412500/hk-social-network-penetration/, last accessed on August 1, 2021). Statista; 2020.

Reference Type BACKGROUND

Kemp S. Digital 2021: Hong Kong (Link: https://datareportal.com/reports/digital-2021-hong-kong, last accessed on August 1, 2021). Data Reportal; 2021.

Reference Type BACKGROUND

Müller J. Social network penetration in Singapore Q3 2020 (Link: https://www.statista.com/statistics/284466/singapore-social-network-penetration/, last accessed on August 1, 2021). Statista; 2020.

Reference Type BACKGROUND

Huang C. Hong Kong faces uphill task to vaccinate its seniors against Covid-19 (Link: https://www.straitstimes.com/asia/east-asia/hong-kongs-uphill-push-to-vaccinate-its-seniors-against-covid-19, last accessed on August 1, 2021). The Straits Times. 2021.

Reference Type BACKGROUND

Steve. Lexicon. The LINE Phenomenon in Thailand - By the Numbers (Link: https://lexiconthai.com/blog/the-line-phenomenon-in-thailand-by-the-numbers/, last accessed on August 1, 2021), 2020.

Reference Type BACKGROUND

Agency T. Line in Thailand Internet Population (Link: https://www.twfdigital.com/blog/2020/04/line-user- stat-in-thailand-2020/, last accessed on August 1, 2021), 2020.

Reference Type BACKGROUND

Get bad news (Link: https://www.getbadnews.com/#intro, last accessed on August 1, 2021). 2021.

Reference Type BACKGROUND

Elkin J. WHO launches a chatbot on Facebook Messenger to combat COVID-19 misinformation. (Link: https://www.who.int/news-room/feature-stories/detail/who-launches-a-chatbot-powered-facebook- messenger-to-combat-covid-19-misinformation, last accessed: August 1, 2021). 2020.

Reference Type BACKGROUND

Larson HJ, Schulz WS, Tucker JD, Smith DM. Measuring vaccine confidence: introducing a global vaccine confidence index. PLoS Curr. 2015 Feb 25;7:ecurrents.outbreaks.ce0f6177bc97332602a8e3fe7d7f7cc4. doi: 10.1371/currents.outbreaks.ce0f6177bc97332602a8e3fe7d7f7cc4.

Reference Type BACKGROUND
PMID: 25789200 (View on PubMed)

SAGE. Report of the SAGE Working Group on Vaccine Hesitancy (Link: https://www.who.int/immunization/sage/meetings/2014/october/1_Report_WORKING_GROUP_vaccine_hesita ncy_final.pdf, last accessed on August 1, 2021), 2014.

Reference Type BACKGROUND

Other Identifiers

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UW 21-659

Identifier Type: -

Identifier Source: org_study_id