跳至主要内容
临床试验/NCT06931782
NCT06931782Enrolling By Invitation不适用

Effectiveness of Artificial Intelligence (AI) in the Prevention, Diagnosis, and Triage of Respiratory Diseases: A Multicenter, Randomized Controlled Study

The First Affiliated Hospital of Guangzhou Medical University1 个研究点 分布在 1 个国家目标入组 2,400 人开始时间: 2025年1月1日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
Enrolling By Invitation
发起方
入组人数
2,400
试验地点
1
主要终点
the accuracy of participants in answering questions related to triage, diagnosis, and risk factor identification of respiratory diseases using artificial intelligence versus internet-based information retrieval assessed by questionnaire survey

研究概览

简要总结

This study will evaluate the impact of using the GPT-4o compared to traditional online tools in the field of respiratory disease prevention, focusing on the dissemination of knowledge and behavior changes among the general public. We will explore the effectiveness of GPT-4o in enhancing public awareness and management capabilities regarding respiratory diseases and promoting appropriate preventive behaviors.

详细描述

Artificial intelligence (AI) technologies, particularly advanced large language models like GPT-4o developed by OpenAI, hold immense potential in enhancing public health education and preventive behaviors. Although GPT-4o was not specifically designed for respiratory disease prevention, it has shown promising prospects in numerous healthcare-related applications, such as providing health information, responding to public inquiries, and supporting health education efforts. However, its effectiveness in improving public awareness and management capabilities regarding respiratory diseases remains to be further explored.

Understanding and managing respiratory diseases involve complex processes, including symptom recognition, application of preventive knowledge, and informed decision-making. Integrating AI tools like GPT-4o into public health education could potentially enhance knowledge dissemination, reduce misinformation, and encourage appropriate preventive behaviors among the general population. Nevertheless, GPT-4o has not been specifically validated for respiratory disease prevention and carries the risk of generating misleading or inaccurate information, which could confuse users. Improper use of such tools may fail to raise awareness and could even lead to counterproductive behaviors. Therefore, studying how large language models like GPT-4o can effectively support public education and behavior change in this context is of critical importance.

In this study, participants will be randomly divided into two groups: one group will have access to Fine-turned GPT-4o, while the other will rely solely on traditional online tools. They will be presented with scenarios related to respiratory diseases and asked to explain their identification of high-risk factors, understanding of diagnoses, and proposed triage actions for each scenario. Each scenario was developed by a panel of three experts in respiratory health, who also established standardized answers. Responses will be evaluated by two independent groups of reviewers unaware of the participants' group assignments. These experts independently created initial scoring criteria and resolved discrepancies through multiple rounds of discussion to ensure consistency and accuracy.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Prevention
盲法
Single (Outcomes Assessor)

入排标准

年龄范围
18 Years 至 75 Years(Adult, Older Adult)
性别
All
接受健康志愿者
是

入选标准

  • •No medical background
  • •Aged from 18 to 75 years old

排除标准

  • •Had a medical background
  • •Exceeds the age criteria
  • •Failed to comply with the survey requirements

研究组 & 干预措施

AI-Assisted Group

Experimental

Participants completed the questionnaire using AI-driven tools for content generation and information retrieval.

干预措施: AI (Other)

Internet-Based Group

No Intervention

Participants completed the questionnaire using standard internet search engines for information retrieval.

结局指标

主要结局

the accuracy of participants in answering questions related to triage, diagnosis, and risk factor identification of respiratory diseases using artificial intelligence versus internet-based information retrieval assessed by questionnaire survey

时间窗: From enrollment to the end of test at 1 hour.

次要结局

  • the accuracy of different subgroups in answering questions related to triage, diagnosis, and risk factor identification of respiratory diseases using artificial intelligence versus internet-based information retrieval assessed by questionnaire survey(From enrollment to the end of test at 1 hour.)
  • Time (in seconds) participants spend per questionnaire between the two study arms.(From enrollment to the end of test at 1 hour.)

研究者

发起方
The First Affiliated Hospital of Guangzhou Medical University
申办方类型
Other
责任方
Principal Investigator
主要研究者

Jianxing He

Professor

The First Affiliated Hospital of Guangzhou Medical University

研究点 (1)

Loading locations...

相似试验

AI in Respiratory Disease Prevention, Diagnosis, and... | 临床试验