Evaluating the Role of ChatGPT in Educating Patients With Early-stage Hepatocellular Carcinoma
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
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
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
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Beitou District
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Taipei, Beitou District, Taiwan, 11217
- Recruiting
- Taipei Veterans General Hospital
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Contact:
- Chun-Ying Wu
- Phone Number: 4190 +886-28712121
- Email: chptaiwan07@gmail.com
-
Contact:
- HSIAO-PING CHEN
- Phone Number: 4190 +886-28712121
- Email: chptaiwan07@gmail.com
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
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
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.
|
Patients receive additional education using a GPT-3.5-based
educational robot on top of the traditional education.
Other Names:
|
|
Active Comparator: Traditional education procedures
Patients receive standard traditional education procedures.
|
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
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
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)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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