利用人工智能增强对疫苗错误信息的认知韧性:来自随机试验的证据
利用对话式人工智能构建对疫苗错误信息的认知韧性:来自英国随机试验的证据
This study aims to understand how parents and caregivers in the United Kingdom engage with information about childhood vaccination (routine vaccines for children and adolescents, excluding tetanus or international travel-related vaccines) and how tailored digital health tools can help address childhood vaccine misinformation.
研究概览
详细说明
Global evidence shows that harmful and misleading information spreads rapidly online and can undermine trust in public health guidance. The World Health Organization has described this challenge as an "infodemic." In the United Kingdom (UK), most people obtain news through online platforms, and false information travels faster and further than accurate content. Vaccination is among the areas most affected. Many UK parents report encountering anti- vaccine claims online, and research shows that such exposure is linked to reduced vaccine confidence and lower uptake.
These concerns arise at a time when routine childhood vaccination rates in the UK have declined below WHO targets, contributing to renewed outbreaks of preventable diseases such as measles. Studies also show that simply providing more factual information is often insufficient to counter misinformation. Cognitive biases - such as confirmation bias, emotional reasoning, and low perceived risk - shape how people interpret health information. Systematic reviews suggest that pre-emptive approaches based on inoculation theory ("prebunking"), which warn people about common manipulation tactics and provide weakened examples of misinformation, can strengthen their ability to recognise and resist false claims.
At the same time, advances in artificial intelligence have created opportunities to deliver personalised, interactive health communication at scale. Emerging evidence indicates that brief conversations with AI-enabled, vaccine-focused chatbots can improve rumour recognition, encourage informed decision-making, and reduce belief in false narratives by providing personalised, interactive, and accessible information. Building on this evidence, this project will test whether an AI-based chatbot can help parents identify misleading claims about childhood vaccinations and increase their confidence in making childhood vaccination decisions.
This study aims to evaluate whether an AI-driven chatbot, MindShield, can strengthen resilience to vaccine misinformation by directly engaging the cognitive biases - such as confirmation bias, affective reasoning, and optimism bias - that shape vaccine risk perception and decision-making. We will first identify bias patterns underlying misinformation beliefs among parents in the UK. MindShield, grounded in inoculation theory, will then be evaluated in a randomised controlled trial to test whether short, bias-aware conversations improve bias recognition, misinformation discernment, and vaccine confidence compared with factual information alone. Finally, we will assess the scalability, acceptability, and ethical considerations of bias-targeted AI interventions for broader misinformation contexts. The study asks whether conversational AI can act as a cognitive safeguard, helping individuals recognise and resist manipulative narratives while supporting informed, confident health decisions.
We will conduct a randomised controlled trial with 1,000 parents or caregivers of children under 18 in the UK. Eligible participants will be recruited online and randomly assigned to either:
- Intervention group: a brief interaction with MindShield, an AI-based chatbot introducing three common misinformation tactics-logical fallacies, emotional manipulation, and risk-perception biases-through short explanations and interactive examples; or
- Control group: a "myth versus fact" infographic adapted from official public health communication materials presenting evidence-based information on the same topics
All participants will complete baseline and immediate post-intervention questionnaires. The primary outcome is parents' ability to correctly distinguish true from false childhood vaccine statements. Secondary outcomes include vaccine confidence, willingness to vaccinate, perceived risks, self-efficacy, and perceptions of AI. Participants in the intervention group will also assess the chatbot's acceptability and usability. Quantitative data will be analysed using mixed-effects models following intention-to-treat principles. The findings will help determine whether an AI-based, vaccine-focused chatbot can strengthen resilience to misinformation and improve informed decision-making around childhood vaccination. A subsequent scale-up to additional countries is planned, intended to evaluate cross-cultural generalizability.
研究类型
注册 (实际的)
阶段
- 不适用
联系人和位置
学习地点
-
-
-
London、英国
- London School of Hygiene and Tropical Medicine
-
-
参与标准
资格标准
适合学习的年龄
接受健康志愿者
有资格学习的性别
描述
Inclusion Criteria:
- Parents or primary caregivers of at least one child under 18 years of age in the UK who is able to answer questions about their child's vaccination status;
- Those who have basic literacy in English;
- Those who have regular access to a digital device and the internet; and
- Those who provide informed consent and agree to participate in the trial
Exclusion Criteria:
- Those who have a visual/reading disability that could prevent their participation in or completion of the study activities
学习计划
研究是如何设计的?
设计细节
- 主要用途:卫生服务研究
- 分配:随机化
- 介入模型:并行分配
- 屏蔽:双倍的
武器和干预
参与者组/臂 |
干预/治疗 |
|---|---|
|
实验性的:AI-driven chatbot
An interactive, web-based, AI-driven chatbot intervention designed to counter vaccine misinformation. It can be accessed via a personal computer, tablet, or mobile device through a web- browser link. |
A tailored AI-driven chatbot designed to counter vaccine misinformation. |
|
有源比较器:Social media infographic
A UNICEF social media infographic with three "myth vs. fact" statements on vaccination that correspond to the same misinformation tactics explained by the MindShield chatbot. |
A UNICEF social media infographic with three "myth vs. fact" statements on vaccination. |
研究衡量的是什么?
主要结果指标
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
|
Parental susceptibility to misinformation about childhood vaccination
大体时间:From enrollment to the endpoint assessment immediately following the intervention during the same survey session (approximately 20-30 minutes)
|
The primary outcome of this study will assess parental susceptibility to misinformation about childhood vaccination, defined as parents' ability to accurately distinguish between true and false vaccine-related information. This will be measured using ten statements on childhood vaccines, including four true and six false, rumour-related statements. Two of the rumour-related statements correspond to each of the three misinformation tactics introduced by the chatbot and the UNICEF infographic. This measure reflects parents' ability to identify misinformation containing manipulation tactics they were inoculated against and to distinguish true from false information regarding childhood vaccination. Responses will be recorded as "True", "False", or "Don't know". A composite misinformation susceptibility score will be calculated based on the number of correct responses, with higher scores indicating greater ability to identify vaccine misinformation accurately. |
From enrollment to the endpoint assessment immediately following the intervention during the same survey session (approximately 20-30 minutes)
|
次要结果测量
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
|
Self-efficacy
大体时间:From enrollment to the endpoint assessment immediately following the intervention during the same survey session (approximately 20-30 minutes)
|
Participants' self-efficacy will be evaluated in two domains: (a) confidence in making informed vaccination decisions for their children, measured with a binary response of "Yes" or "No", and (b) confidence in seeking trustworthy information about childhood vaccinations, measured on a four-point scale from "Not at all confident" to "Very confident". |
From enrollment to the endpoint assessment immediately following the intervention during the same survey session (approximately 20-30 minutes)
|
合作者和调查者
研究记录日期
研究主要日期
学习开始 (实际的)
初级完成 (实际的)
研究完成 (实际的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
此信息直接从 clinicaltrials.gov 网站检索,没有任何更改。如果您有任何更改、删除或更新研究详细信息的请求,请联系 register@clinicaltrials.gov. clinicaltrials.gov 上实施更改,我们的网站上也会自动更新.