This study aims to develop and examine the feasibility and preliminary effectiveness of an AI-based sarcoma chatbot building on ChatGPT (ASCC) to address the information needs of sarcoma patients. We hypothesized: 1) the ASCC will demonstrate good usability; 2) the study will be feasible in terms of all feasibility indicators; 3) the experimental group will report improved satisfaction and self-efficacy, decreased anxiety and stress than the control groups upon completion of the intervention. The ASCC will be developed using a co-design approach. A pilot randomized controlled trial will then be conducted in the three oncology wards of collaborative hospitals. Seventy-eight sarcoma patients will be recruited and randomized to the experimental group (n=39) and the control group (n=39). The experimental group will use the ASCC available 24/7 via voice or text for disease-related questions for one month while the control group will receive usual care.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
SINGLE
Enrollment
78
The participants in the experimental group will access the ASCC via a webpage alongside standard information from health professionals for one month (15 minutes weekly).
Participants in the control group will receive routine clinical care, including standard information from doctor-patient consultations (e.g., diagnosis, treatment, medical tests) and hospital provided sarcoma and treatment leaflet.
Screening rate
Calculated by dividing the number of sarcoma patients screened by the research team by the number of sarcoma patients.
Time frame: During the enrollment period of this project.
Eligibility rate
Calculated by dividing the number of participants who are eligible by the number who are screened.
Time frame: During the enrollment period of this project.
Consent rate
Calculated by dividing the number of participants who were randomized into intervention and control groups by those provide consent.
Time frame: During the enrollment period of this project.
Randomization rate
Calculated by dividing the number of participants who consent to join the study by the number who are eligible.
Time frame: During the enrollment period of this project.
Attendance rate
Calculated by dividing the number of participants who complete the intervention by those who are randomised
Time frame: Baseline and immediately after intervention (T1)
Retention rate
Calculated by dividing the number of participants who remain in the study by those who are randomized. This will be calculated by groups.
Time frame: Baseline and immediately after intervention (T1)
Completion rate
Calculated by dividing the number of participants who returned questionnaires by the number of questionnaires distributed. Calculated by dividing the number of participants who remain in the study by those who are randomized. This will be calculated by groups.
Time frame: Baseline and immediately after intervention (T1)
Proportion of missing data
Calculated as the percentage of missing values in the dataset. Unknown or blank values will be considered missing values.
Time frame: Baseline and immediately after intervention (T1)
Adverse events
Adverse events are defined as unfavourable and unintended events that are not present, or appear to have worsened during the study.
Time frame: immediately after intervention (T1)
Information satisfaction
The EORTC QLQ-INFO25 will be used to evaluate participants' satisfaction with the information received. A four-point Likert scale is used to score 25 items ('nothing' = 1 to 'a lot' = 4), with higher scores indicating greater information satisfaction.
Time frame: Baseline and immediately after intervention (T1)
Anxiety and stress
The Depression Anxiety Stress Scale-21 (DASS-21) will be used to assess anxiety and stress.(36) 21 items are scored using a four-point Likert scale, with higher score indicating more severe symptoms.
Time frame: Baseline and immediately after intervention (T1)
Self-efficacy
Self-efficacy will be assessed using the Strategies Used by People to Promote Health (SUPPH) with good reliability and validity. This 28-item likert scale measure self-care self-efficacy, with higher scores indicating more positive perceptions of self-efficacy.
Time frame: Baseline and immediately after intervention (T1)
System Usability Scale
System Usability Scale (SUS) will be used to measure the usability of digital health solutions by 10 items rated on a 5-point Likert scale from 0-100. The chatbot will be considered highly usable if the mean score exceeds 68.
Time frame: immediately after intervention (T1)
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.