Evaluating the Role of ChatGPT in Educating Patients With Early-stage Hepatocellular Carcinoma

April 22, 2024 updated by: Taipei Veterans General Hospital, Taiwan

Liver cancer is a leading cause of cancer-related deaths in Taiwan, with its onset linked to factors like chronic liver conditions, cirrhosis, and genetic predispositions. According to the "Barcelona Clinic Liver Cancer (BCLC)" classification, early-stage liver cancer is demarcated by stages 0 to A. Upon such diagnosis, both patients and their families often have numerous questions and concerns, ranging from treatment choices to long-term outcomes. The research proposes a GPT-3.5-based chatbot to assist these patients by providing timely, personalized information, aiming to enrich their understanding of the disease and improve communication between patients and health professionals.

The research methodology employs a Randomized Controlled Trial (RCT) design, dividing participants into a control cohort receiving standard patient education routine and an experimental cohort receiving both the AI chatbot and traditional education routine. The comparative analysis of these cohorts will determine the effectiveness of the AI intervention in improving patients' health literacy and satisfaction.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Liver cancer is the second most common cause of cancer-related deaths in Taiwan. Various factors play a role in its development, such as chronic liver conditions, cirrhosis, viral infections, alcohol intake, obesity, diabetes, and genetic predispositions, among others. Based on the "Barcelona Clinic Liver Cancer (BCLC)" system, early-stage liver cancer falls within stages 0 to A. When faced with an early-stage liver cancer diagnosis, patients and their relatives frequently express concerns. These may range from the potential effects of the disease on daily living, evaluating treatment options, potential side effects, costs involved, the chances of recurrence, and survival rates, to the care required after the treatment. Addressing these worries often requires extensive explanations and time for the patients to process the information.

The research proposes using a chatbot built upon the GPT-3.5 language model developed by OpenAI for patient education services. Such a chatbot would aid early-stage liver cancer patients navigate the complexities of obtaining relevant information. As an artificial intelligence technology, the chatbot can offer timely, personalized information and psychological support. By responding to patients' inquiries, the chatbot can provide a thorough understanding of basic liver cancer knowledge, its causes, and treatment approaches, thereby facilitating a deeper comprehension of the early stages of liver cancer and its treatment regimen. Patients and their relatives can comprehend their condition and treatment plans, enhancing their conversations with medical staff and promoting a harmonious doctor-patient relationship.

The research uses a Randomized Controlled Trial (RCT) methodology, dividing patients into a control group undergoing the conventional patient education routine, and an experimental group that leverages both the chatbot and traditional education. By comparing selected outcomes between the two groups, the experiment's effectiveness will be determined.

Study Type

Interventional

Enrollment (Estimated)

450

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 Locations

  • Taiwan
    • Beitou District
      • Taipei, Beitou District, Taiwan, 11217
        • Recruiting
        • Taipei Veterans General Hospital
        • Contact:
        • Contact:

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

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Patients with early-stage hepatocellular carcinoma from both gastroenterology and general surgery outpatient departments were included. Early-stage hepatocellular carcinoma is defined based on the Barcelona Clinic Liver Cancer (BCLC) staging as stages 0 to A.

Exclusion Criteria:

  • Patients under the age of 18 or those currently undergoing treatment for other cancers.

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: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: GPT-3.5-based educational
Patients receive additional education using a GPT-3.5-based educational robot on top of the traditional education.
Behavioral: ChatGPT
Patients receive additional education using a GPT-3.5-based educational robot on top of the traditional education.
Other Names:
  • Add GPT-3.5 model for patient education
Active Comparator: Traditional education procedures
Patients receive standard traditional education procedures.
Behavioral: patient education with traditional methods.
Patients receive standard traditional education procedures.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Health literacy score of patients
Time Frame: 1 weeks to 1 month
Primarily measured using the Liver Cancer Knowledge Scale. The scale consists of 20 questions with options including correct, incorrect, and unsure, with 14 correct answers and 6 incorrect ones (questions 4, 7, 11, 15, 18, 19). Each correct answer scores 5 points, while incorrect or unsure answers score 0 points. The score range is from 0 to 100, with a total score of 100 points.
1 weeks to 1 month
Satisfaction score with medical care
Time Frame: 1 weeks to 1 month
It mainly includes satisfaction with traditional health education and AI-based health education tools. The Likert scale assessed the score, which offers options ranging from very dissatisfied (1) to very satisfied (5).
1 weeks to 1 month

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Degree of patient anxiety
Time Frame: 1 weeks to 1 month
Measured using The GAD-7 questionnaire, a scale designed to assess anxiety levels.
1 weeks to 1 month

Collaborators and Investigators

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

Sponsor

Taipei Veterans General Hospital, Taiwan

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 (Actual)

March 22, 2024

Primary Completion (Estimated)

November 29, 2024

Study Completion (Estimated)

March 21, 2025

Study Registration Dates

First Submitted

April 16, 2024

First Submitted That Met QC Criteria

April 22, 2024

First Posted (Actual)

April 25, 2024

Study Record Updates

Last Update Posted (Actual)

April 25, 2024

Last Update Submitted That Met QC Criteria

April 22, 2024

Last Verified

April 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2023-11-005A

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

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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