Vaccine Chatbot for Improving Influenza Vaccination Uptake

October 23, 2024 updated by: Zhiyuan Hou, Fudan University

AI-enabled Vaccine Chatbot for Improving Influenza Vaccination Uptake in Children: a Cluster Randomized Trial

This study aims to assess the impact of a vaccine chatbot on improving influenza vaccination uptake among children aged between 6 and 59 months through a cluster randomized trial. Specifically, the main questions it seeks to answer are whether an AI-enabled vaccine chatbot will increase the uptake of influenza vaccine among children and their family members, and how it will influence parents' literacy and confidence towards influenza vaccine. It will explore the potential role of vaccine chatbot on vaccination services.

A cluster randomization will be used to assign children to the intervention and control groups. Parents of children in the intervention group will be invited to use the influenza vaccine chatbot online through WeChat, the mostly widely used social media platform in mainland China, or any web browsers. They can ask any questions related to the influenza vaccine and receive validated answers from the chatbot immediately. The intervention will last one and a half months, with invitations sent every ten days to reinforce the engagement. The control group will not use the chatbot during the intervention duration. After the intervention, the uptake, literacy, and confidence towards influenza vaccine will be compared between the intervention and control groups to evaluate the impact of vaccine chatbot.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

This is a cluster randomized trial (CRTs) consisting of two arms to evaluate the effectiveness of an AI-enabled vaccine chatbot on influenza vaccination uptake among children aged between 6 and 59 months. Participants regularly visit primary care clinics when they are invited to participate in this trial, and with clinic-days as clusters, a cluster randomization will be used to assign clinic days to the intervention and control groups.

The sample size is calculated based on the primary outcome - the influenza vaccination uptake among children, and the main analysis method, which involves the comparison of differences in vaccination rates between the intervention and control groups after the intervention. According to the vaccination data of study sites, the uptake of influenza vaccine among children aged 6-59 months is around 20% in the previous flu season. In China, influenza vaccination starts in September, and has been available for two months before this trial. Therefore, we assume that the baseline vaccination rate is 10% without the intervention during this trial, and the chatbot intervention would raise this rate by 6 percentage points to 16% at least. We assume a cluster size of 15 children per day per clinic based on routine visiting data. To have 80% power to detect a difference between the group proportions of 0.06, it requires 35 clusters and 525 participants per arm, assuming an intracluster correlation coefficient of 0.005 and a two-sided test with the 0.05 significance level. Assuming at least 10% loss to follow-up, the sample size is 600 participants per arm and 1,200 in total.

Multi-stage sampling will be utilized. Firstly, three representative regions (an urban district, a suburban district, and a rural county) will be selected to represent different economic development levels in China. In each region, four clinics will be selected based on geographical location, economic development, and patient volume. In each clinic, the 6-8 working days will be chosen to conduct this trial, resulting in 72-96 clinic-days (clusters) in 12 clinics in total. In these selected clinic-days, children and their parents regularly visit primary care clinics. All eligible children presenting in the selected clinic-days will be invited to participate by medical staff, and one of their parents will be included in this trial.

Stratified cluster randomized grouping will be employed. All clinic-days will be randomly allocated into intervention group or control group at a 1:1 ratio, stratified by region and clinic, resulting with 36-48 clinic-days per arm. Approximately 400 participants (200 in intervention group; 200 in control group) are expected to participate in this trial in each region, with a total sample size of 1,200 participants, meeting the sample size requirement.

The intervention group will engage with influenza vaccine chatbot for one and a half months, while the control group will receive the standard of care according to the local context, without additional intervention. On the day of the visit, the intervention group will be invited to use the influenza vaccine chatbot online through WeChat or any web browsers, where they can ask any questions related to the influenza vaccine and get validated answers from the chatbot immediately. Staff will be on site to help them use vaccine chatbot for the intervention group. Then, during the 1.5-month intervention, participants in the intervention group will be informed that the chatbot is available for use at their convenience, with coordinators sending the chatbot link every ten days to remind them to use. Conversely, the control group will not use the chatbot, without additional intervention during the trial, but will gain access after the trial ends.

At the end of the 1.5-month intervention, all participants from both intervention and control groups will be invited to complete a questionary survey. Three months after the intervention begins, influenza vaccination status of children and their parents will be collected from the vaccination registration system of local CDCs.

Difference in outcomes between the intervention and control groups will be assessed using t-tests and/or analysis of variance (ANOVA) for normally distributed continuous variables, and the Chi-square or Fisher's exact test will be used for categorical variables. When continuous variables do not meet normal distribution, the Wilcoxon rank-sum test will be employed. Multivariate regression models will be employed to evaluate the effectiveness of the chatbot intervention on the primary and secondary outcomes, adjusting for potential confounders. Given that participants in the intervention group will have varying frequencies and durations of using the chatbot, a dose-response relationship will be employed to evaluate the intervention effects by intervention intensity.

Study Type

Interventional

Enrollment (Estimated)

1200

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • China
    • Zhejiang
      • Hangzhou, Zhejiang, China, 310025
        • Hangzhou Center for Disease Control and Prevention
        • Contact:
        • Contact:
          • Wenwen Gu, MS

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Parents of the child visiting clinics.
  • Children aged between 6 and 59 months.
  • Children who have not received an influenza vaccine in both the current and previous flu seasons and have not yet made an appointment for an influenza vaccine.
  • Children who have no contraindications to receiving an influenza vaccine.
  • Provide informed consent and willing to participate throughout the study.

Exclusion Criteria:

  • Children vaccinated or appointed for influenza vaccination or with any contraindication to influenza vaccine.
  • Parents with mental disorders or visual/reading impairments, and unable to cooperate with and undergo the intervention activities.
  • Unwilling to participate.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Double

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
No Intervention: Control group
The control group will not use the chatbot during the intervention duration.
Experimental: Influenza Vaccine Chatbot Intervention group
In this arm, participants will receive a vaccine chatbot intervention for one and a half months. The AI-enabled influenza vaccine chatbot can be accessed online through WeChat or any web browsers, where people can ask any questions related to the influenza vaccine and get previously validated answers from the chatbot immediately. The chatbot is available for use at their convenience during the 1.5-month intervention, with invitations sent every ten days to reinforce the engagement.
Behavioral: An AI-enabled chatbot tailored for influenza vaccine consultation
The AI-enabled influenza vaccine chatbot can be accessed online through WeChat or any web browsers. The foundation of this chatbot is an expansive knowledge database, constructed with information sourced exclusively from healthcare authorities such as China CDCs and Health Departments, and thoroughly verified by public health experts. This database integrates data on the disease's burden, susceptibility, and severity, along with in-depth details about the vaccines, including their importance, efficacy, safety, and recommended demographics and timing for vaccination. It also covers types and costs of vaccines, societal norms such as vaccination guidelines, expert recommendations, and vaccination trends both in China and internationally. It also includes misinformation and fact-checking contents and provides information about vaccination services such as locations and appointment scheduling.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Influenza vaccination uptake for children
Time Frame: 1.5 months and three months
whether the enrolled children receive an influenza vaccine. It will be measured in the survey at the end of the 1.5-month intervention, and be recorded from the vaccination registration system three months after the intervention begins.
1.5 months and three months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Influenza vaccination uptake for children's family members
Time Frame: 1.5 months and three months
whether children's family members receive an influenza vaccine. It will be measured in the survey at the end of the 1.5-month intervention, and be recorded from the vaccination registration system three months after the intervention begins.
1.5 months and three months
Influenza vaccination-specific consultation
Time Frame: 1.5 months
whether parents consult health professionals about vaccinating their children with influenza vaccine during the 1.5-month intervention period, collected in the survey at the end of the 1.5-month intervention.
1.5 months
Influenza vaccine literacy
Time Frame: 1.5 months
A series of ten questions about influenza vaccine knowledge and misinformation, collected in the survey at the end of the 1.5-month intervention. Total literacy score is calculated based on the number of questions answered correctly by the participants.
1.5 months
Influenza vaccine confidence
Time Frame: 1.5 months
Vaccine Confidence Index, which evaluates parental perceptions of the vaccine's importance, effectiveness, and safety, collected in the survey at the end of the 1.5-month intervention.
1.5 months
Sustained vaccination intention
Time Frame: 1.5 months
Whether parents intend to vaccinate their children against influenza in the next flu season, collected in the survey at the end of the 1.5-month intervention.
1.5 months

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Cost of chatbot intervention
Time Frame: 1.5 months
The cost of designing vaccine chatbot and implementing chatbot intervention
1.5 months
Chatbot Usability
Time Frame: 1.5 months
A series of questions assessing usability and feasibility, fairness and safety, user experience, and overall assessment of the chatbot.
1.5 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Fudan University

Investigators

  • Principal Investigator: Zhiyuan Hou, PhD, School of Public Health，Fudan University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

October 26, 2024

Primary Completion (Estimated)

February 15, 2025

Study Completion (Estimated)

March 31, 2025

Study Registration Dates

First Submitted

October 23, 2024

First Submitted That Met QC Criteria

October 23, 2024

First Posted (Actual)

October 24, 2024

Study Record Updates

Last Update Posted (Actual)

October 24, 2024

Last Update Submitted That Met QC Criteria

October 23, 2024

Last Verified

October 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • Fudan Univeristy

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Individual participant data that underlie the results reported in the article, after de-identification (text, tables, figures, and appendices), will be shared upon reasonable requests. A written data-sharing request for meta-analysis should be submitted by email with a methodologically sound proposal. Proposals should be directed to zyhou@fudan.edu.cn; to gain access, data requestors will need to sign a data access agreement.

IPD Sharing Time Frame

Beginning 12 months and ending 36 months following article publication

IPD Sharing Access Criteria

Researchers who provide a methodologically sound proposal for meta analysis. Proposals should be directed to zyhou@fudan.edu.cn; to gain access, data requestors will need to sign a data access agreement.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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