Evaluating the Role of ChatGPT in Educating Patients With Early-stage Hepatocellular Carcinoma
- Conditions
- Carcinoma, Hepatocellular
- Interventions
- Behavioral: ChatGPTBehavioral: patient education with traditional methods.
- Registration Number
- NCT06384950
- Lead Sponsor
- Taipei Veterans General Hospital, Taiwan
- Brief Summary
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.
- 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.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 450
- 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.
- Patients under the age of 18 or those currently undergoing treatment for other cancers.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Arm && Interventions
Group Intervention Description GPT-3.5-based educational ChatGPT Patients receive additional education using a GPT-3.5-based educational robot on top of the traditional education. Traditional education procedures patient education with traditional methods. Patients receive standard traditional education procedures.
- Primary Outcome Measures
Name Time Method Satisfaction score with medical care 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).
Health literacy score of patients 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.
- Secondary Outcome Measures
Name Time Method Degree of patient anxiety 1 weeks to 1 month Measured using The GAD-7 questionnaire, a scale designed to assess anxiety levels.
Trial Locations
- Locations (1)
Taipei Veterans General Hospital
🇨🇳Taipei, Beitou District, Taiwan