AI in Hypertension Treatment Education: Comparing GPT and Traditional Methods

NCT ID: NCT06776354

Last Updated: 2025-12-09

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 52 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-10-20
• Study Completion Date: 2025-07-30

Brief Summary

Educational Trial: GPT-Based Training vs. Traditional Teaching for Hypertension Management

The goal of this educational trial is to determine whether a Generative Pre-trained Transformer (GPT)-based training system is more effective than traditional teaching methods in helping medical students master hypertension management plans. It will also evaluate the educational effectiveness and engagement of the GPT-based system. The main questions it aims to answer are:

Does the GPT-based training improve the ability of students to develop effective hypertension management plans compared to traditional methods? How do students perceive the use of the GPT system in their learning process? Researchers will compare the GPT-based training system to traditional teaching methods to see if the innovative AI approach enhances learning outcomes in medical education.

Participants will:

Engage with either the GPT-based system or traditional teaching materials. Visit the educational facility periodically for assessments and feedback sessions.

Keep a diary of their learning experiences, noting any difficulties or advantages they observe in the training method they are assigned.

Conditions

Medical Education; Hypertension; GPT

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: OTHER
• Blinding Strategy: NONE

Study Groups

GPT-based training

Generative Pre-trained Transformer (GPT)-based training system

Group Type: EXPERIMENTAL

GPT-based training

Intervention Type: BEHAVIORAL

GPT-based training whether could improve the ability of students to develop effective hypertension management plans

traditional training

traditional training method

Group Type: ACTIVE_COMPARATOR

traditional training

Intervention Type: BEHAVIORAL

traditional teaching methods

Interventions

GPT-based training

GPT-based training whether could improve the ability of students to develop effective hypertension management plans

Intervention Type: BEHAVIORAL

traditional training

traditional teaching methods

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

• Graduate or regulatory trainee, currently rotating in cardiology and willing to participate in research.
• Age between 18-30 years old, gender not limited.
• No specialized training experience in hypertension diagnosis and treatment, only possessing basic medical theoretical knowledge.
• Able to accept a 4-week teaching intervention (2 hours of study per week).
• Sign the informed consent form and be aware of the research purpose and process.

Exclusion Criteria

• Graduate students or trained interns who have received specialized training in hypertension medication treatment.
• Students unable to complete the full course of study (e.g., rotations shorter than four weeks or potential mid-course withdrawal).
• Unable to consistently participate in educational interventions (e.g., conflicts with study schedule).
• Have severe physical or mental health issues that may affect the learning process.
• Have language comprehension barriers or cognitive impairments, making it difficult to complete learning tasks.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 30 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

zhen wang

OTHER

Sponsor Role: lead

Responsible Party

zhen wang

physician-in-charge

Responsibility Role: SPONSOR_INVESTIGATOR

Principal Investigators

xianrui luo

Role: STUDY_CHAIR

The Second Hospital of Anhui Medical University

Locations

678 Furong Road, Economic Development Zone, Hefei City, Anhui Province, China

Hefei, Anhui, China

Countries

China

Other Identifiers

2023jyxm1150

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

2023jyxm1150

Identifier Type: -

Identifier Source: org_study_id