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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

450 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-03-22

Study Completion Date

2025-03-21

Brief Summary

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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.

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Detailed Description

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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.

Conditions

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Carcinoma, Hepatocellular

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

To compare the educational effectiveness of a chatbot integrated with health education information to traditional health education methods. This comparison encompassed aspects such as the patient's health literacy and clinical satisfaction. Based on the findings, recommendations and improvements would be proposed to promote the application and development of large language models in the medical field.

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

SINGLE

Participants

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 Groups

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GPT-3.5-based educational

Patients receive additional education using a GPT-3.5-based educational robot on top of the traditional education.

Group Type EXPERIMENTAL

ChatGPT

Intervention Type BEHAVIORAL

Patients receive additional education using a GPT-3.5-based educational robot on top of the traditional education.

Traditional education procedures

Patients receive standard traditional education procedures.

Group Type ACTIVE_COMPARATOR

patient education with traditional methods.

Intervention Type BEHAVIORAL

Patients receive standard traditional education procedures.

Interventions

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ChatGPT

Patients receive additional education using a GPT-3.5-based educational robot on top of the traditional education.

Intervention Type BEHAVIORAL

patient education with traditional methods.

Patients receive standard traditional education procedures.

Intervention Type BEHAVIORAL

Other Intervention Names

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Add GPT-3.5 model for patient education

Eligibility Criteria

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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.